Hi, everyone. Welcome to More Than Numbers live, the show folks on turning data teams from support functions into engines of growth. I'm Ollie Hughes. I'm one of the cofounders of Calm dot co. We're a Canvas based BI tool. We're all about turning data teams from, dashboard factories into their organization's problem solvers. Each week, I have the pleasure of interviewing a data industry leader looking to turn their data team into value engines. And this week, I'm so pleased to invite, Thibaut, Arbez, Dupree. Sorry, Thibaut. I've completely destroyed your name here, but you forgive me, I hope. Thank you so much for joining me today. No worries. I practice it. I'm still lazy I've always I've always made it, and then it kind of all fell away at the end. So, actually, let me choose you properly, though. So, Tivo, you are the VP of business performance at Deezer. Deezer is one of the one of those amazing, streaming applications you may know. You have a half a billion euro turnover over that. You're it's an amazing data organization as you can probably imagine. I can't imagine the datasets you have to play with. It must be amazing. Your background before that, you were actually in banking and m and a, so you've got a bit of a amazing breadth of career so far. And today, we're gonna talk about how you you're using the data or get diesel to drive business performance and become the problem solving of the organization, which is a really amazing topic for us as you can imagine. So thank you very much for being here. Pleasure. So before we get going into the meat of this, I just wanna, give you a bit more of your background. So I've teed up before, you bit of, bit of banking before that, and then obviously now running, the data or get these. Though we'll talk about the name in a second. Maybe the first question to ask is a bit more do we have a joke one? Like, what is your favorite what's been your favorite BI tool? What was the tool that you used other than Excel, which I know you probably use a lot in banking, that you really fell in love with, that really helped you get into data more? Well, Excel is probably still my favorite tool. I mean, we use BigQuery. I I mean, we use a bit of Tableau, but it's probably not my I mean, I prefer working with the numbers directly, I suppose. So I I find I mean, I haven't tried any others, but I find BigQuery pretty useful, pretty organized and easy to use. That's I mean, that's so that's that's great. I mean, that's the Well, I mean, unless you're talking about visualization only, which is then that's probably not the right answer. But No. That's good. We'll take the we'll take I think we're pooing your, like, your financial credentials here, but I just wanna see tables of numbers. Yeah. I mean, basically. If, if you could ask you if you if I you obviously have come from banking into into technology, into data. Tell us about that transition. Like, what made you, like, wanna go that route? That is mainly not a typical route, but it's an interesting Nice stuff. Well, I mean, it wasn't like a plan. I've been doing m and a for a while. I mean, I quite enjoyed it, but it was a lot of work. And then I was I was in a strata at the time, and I wanted to move to Paris. And then there was an opportunity to do kind of strategy m and a, the tech company. And so I joined then initially as a chief of staff, to an exec, and that was really good to kinda get a broad overview. We and it was a lot I mean, I learned a lot because actually in m and a, I was doing large cap oil and gas mining, so very different kind of industries. And it was, I mean, partly, honestly, it was like a lifestyle thing. And then was in tech doing kind of, yeah, as I said, strategy, more strategy, business development, m and a. And then it just kind of so happened. There was an there was a reorg. The opportunity came up to take over this, I don't know, somewhat unloved, product analytics team. And so and there was a need for a kind of from from the from a new CEO, there was a need for a to kinda, you know, someone to push like a a cultural change to make the business a bit more data driven. And so I took the opportunity, but it wasn't part of a plan or anything. I when I joined, I was running around, like, no idea what was going on. Had to restructure the team, had to hire recruit, had to retrain, had to change the relationship that we have with our stakeholders. And I had no idea what I was doing. So, I mean, it was quite fun and easy for a while, and then things started to kind of fit into place. I think a lot of the things that I brought to I mean, I went from managing like one person to managing twenty overnight, and I I brought, I suppose, the experience that I had from banking and from professional services generally, into the team, meaning the way that I recruited, what I was looking for, the way I structured the team, the way we worked with stakeholders, and also the way that I promoted. And it actually, well, I think it seems to work. I mean, we've got good retention. Things have kind of fallen into place. The team's just only gotten bigger. Our scope has gotten bigger. My scope's gotten bigger. And then we've I think we've done pretty well. You you you think you're you know what? I find the story about, how you got into data and how you got hit. You've stumbling stumbling is often a verb I hear. Like, I didn't really end up start. My plan wasn't to be here, but I've just ended up here anyway. And it's great. And and it's just like, basically, people love problem solving, just end up their way to this position. I think if you if you like strategy, you but you actually wanna be kinda closer to the action, it's a really good place to be because you you work with all the teams and there's you you you can kind of I mean, I broadly think of strategy two ways. It's like corporate strategy, which is, you know, maybe a longer term plan. It might involve m and a, might involve new markets and things like that. But then there's operational strategy, which is a much more immediate and depending on the business, depending on where you are in your cycle, it can be a lot more effective, and depending on your industry. Yeah. And data I think running a data team that's centralized and working across the business is probably the best position. Maybe not the best, but, you know, one of the best positions, I think, to be in if you wanna drive operational change and if you wanna understand, the operations of the business and how that drives value, I mean, down through the whole p and l. I think in so we're gonna come onto this because this is why I want desperate to speak to you for so long because I'm not the excitement you described there that the potential, the impact, the scope that you have, what you just laid out there, I don't think many data teams feel that. I don't think many data teams feel that they have that scope of change, that breadth as a positive. So let's I wanna dig into that more. We'll come on to that in a second. But first, let's just orientate like, give people a bit of a sense of Deezer and, like, like, just a bit of the the stack. We call it, like, we call the segment, like, Telogis stack. So just give us a sense. So Deezer, I think, like, we obviously, streaming app is there. How can you help us orientate the audience to, like, what it is that your world looks like a bit like now at a high level? Well, we use, GCP and then BigQuery, as I mentioned. And then visualization, we're using mostly Tableau. I would say ninety percent Tableau, ten percent Looker. The double whammy as I call it. Yeah. I mean, that's the basically, the way I explained it to, to an exec the other day is we use Tableau and then we build look at tables of people who refuse to use Tableau. And then we actually still do reports in, in Google Sheets. I'm I mean, actually, more and more, but really for, I'd say, you know, like, exec level reporting. But it's just kind of a bit quicker for them to get to it's you know, you'll they let you leave the tab open, and it's refreshing every week, and you get, like, the real key business numbers. And we find that people kind of are better at following that than they are with Tableau even if you get, like, you know, the email report. So, I mean, we kinda do what it is necessary to be effective, with the with the audience. But, yeah, in terms of when we're doing analysis and when we wanna use it ourselves, then I think Tableau is the main tool that we use. That's great. And so the thing I wanna start off, because I we wanna I wanna get into the way that you work, the way that your team is positioned, like, as the organization's problem solvers are almost we can certainly I think you've described to me in the past as, like, the internal consultancy, and I think that's an aspiration that most people have. They wanna be that high octane. They wanna be that close. And one of the things that is already different in the just so you can see from your title is that you're you're VP of business perform performance. Right? You're not you're not ahead of data despite the org being full of data engineers, analytics engineers, data scientists, and analysts. And that the structure but your title is different. Like, tell us maybe to start off as we dig into more how you work. Just explain that that that team that team name Yeah. That comes from. It's evolved it's evolved a bit over time, but we've now kind of a kind of clear distinction between I mean, what we say internally that's a bit loose, I guess, is like the more technical teams and the more business focused teams. And so we have a VP of engineering. He's got a bunch of, engineering teams under them who are including data engineers. We have like an innovation team that has a bunch of machine learning, engineers and data scientists. The difference is, so that's like an old difference. So we're under the chief revenue officer. So already, like, that positioning kind of sets the tone. How did it evolve like that? I mean, I obviously came in not being technical at all, and I'm still not particularly. So I came in and, you know, that's the reason I took that took the job was because I wanted to, make operational change to improve the business. I'd I'd been a stakeholder of the previous team, as chief of staff, you know, working on strategy and stuff. And I had kind of noticed a lot of, let's say problems or, you know, maybe not problems or things that could have been better or things that I, you know, I would've done differently. Let's maybe put it that way. And then it's kind of, you know, the I mean, a lot came from the changes at the top as well. Like, I mean, our CEO has changed a few times, and I think we've generally become more and more data focused at that level as well. And that's just, you know, because I I think CEOs come I I mean, people running tech com tech companies now, particularly at scale up level, are generally coming in. Let's say they've had experience at another one or maybe at Amazon or, you know, a big tech company or whatever their background is. They're usually, I think, more and more data focused. And so you kinda gotta go with them, and that's a good thing. And data focused, I mean, it's a it's like a bit of a buzzword. It really just means, like, the logical, quantitative and use deductive reasoning to make decisions in the company. And some and it's a bit meaningless to say data focused. But we so that that was kind of the idea from the start, but it took, you know, it took time because you've got you've got to, like, build trust with stakeholders who have been running their business a certain way. You might wanna change the way they run their business, and that's, like, you know, a constant battle. And Yeah. Yeah. It's a stop in the journey. Yeah. Yeah. Yeah. That and that that kind of you you build that trust. But if there's like a, you know, change in personnel in that team, you know, you might have to re go through that again. And so that's that's kind of a constant thing, and you need to balance that. But I think when you get results, when you can show stakeholders that you bring value, that they meet their objectives because of your help, then, you start to build that trust. But I I wouldn't say that we're, like, necessarily perfect at it, but it's it's gone pretty well. I think you wouldn't be doing a good job if you thought you were perfect, to be honest with you. That's kind of a kind of part of the game. Let's that that's just great. Let let's let's let's bring this in a bit more in a bit more because people must be really people will be really intrigued to hear this. I mean, one of the things that you just said, which I think is totally a huge part of this is the way that you work is so different that when a new, like, a new team leader comes in who you're working with has to relearn the way to work with you because from my beliefs in general is that data teams the function of a data team is so it has so much more breadth than, say, across the industry, across technology, or any any organization. Like, you know, whereas finance or product or marketing have well defined responsibilities, in data, it can be so varied. And so you get someone coming in, and they think they should work with you like you used to go with their old data team in their old organization. You gotta reexplain it. So that reeducation piece is probably quite a helpful insight itself. Just people thinking about they have to constantly remind people the data team's role because we're there is a a a looser definition in the industry as a whole. But let's so let's come back to this. I wanna share on the tenant slide. I know we spoke about the tenants about a year ago, and I and this is what I'm waiting to say just to get you on the show because this is what you know, you helped form these these tenants and help us think of this through. The tenants are, you know, fourfold. So there's operational clarity, seeking that give the business sets make business feel simple, make the business feel structured, not just throughout numbers, solving business problems, minimizing time to decision, and measuring yourself. And, really, I think a lot of what you're gonna be we're gonna be talking about, I guess, is is about how your team works through these four, but particularly as pioneering as the problem solving function. Right? So can you just talk us through maybe at a high level, like, how it is that you your teams works, thinks, and how they engage with the business? Like, how have you made that change when you start, you know, now and how they operate? I think that the four tenants, like, very, yeah, very closely aligned with the way we try to work with our teams. I think the way I I have, like, a slide somewhere, you know, that I pull out when I need to kind of introduce the team to somebody. And it, and it essentially aligns with that. I think we say define objectives, define initiatives, iterate, and then achieve objectives. But, I mean, really what that and that really aligns with the tenants. They're off the screen now, so I'm trying to remember that. But the, you know, that kind of, I've got them written somewhere. So the seeking operational clarity is yeah. Okay. They're back. Thank you. So seeing operational clarity is probably it sounds like the one that, you know, you wouldn't need to work on. It's like, well, you know, we know what we need to do. We know we wanna make more money or whatever, or I, you know, I know what I'm doing at work. It's actually probably that the mo it's the most important one, I think. I agree. At least in my experience, and it probably depends a bit on your business as well, but at least in my experience, it's the most important one. And you'd be amazed at how quickly you can start. You you realize people are you yourself or other people are working on things that actually are not that relevant. And, you know, there's always conversations about OKRs and whatever. And there's one thing to define them, but there's another to really stay focused. So for us, I always say like focus. The that's like the word I use the most is is focus. And you can really help in a data team or, you know, at this point, data slash FP and a, whatever, something who's quantitative, and related to performance, you can help because you wanna pull out the key drivers that, that are also actionable, and then you wanna track how you're going on those. And that, that is kind of, you can see that little diagram there and, and actually the way you present it to people. So whether it's in, you know, a tree diagram or whether it's whatever that can actually make an impact, and it seems silly, but it's a really big deal. I I think people miss on completely underestimate the the power of clarity. Like, if you think about the executive team at any business, they are swamped with information from every side at every level of detail. And if the data teams are all set up There's, like, a number of things going on. I mean, I think the executive one, I think people assume that their boss is, like, a kind of god and knows so much more than them because it's their boss, and it's just not the case at all. Like, they know if anything less than the they're juniors. And so people are like, oh, this, this, and this, and this, and then it was like, oh, yeah. Okay. And they assume the focus will always come down from the top and it should, but you need to really guide that process as well. The whole anyway. A hundred percent. Because, you've gotta make that I mean, that can start really at even the very junior level. You know, the way you're presenting feedback to somebody, if you yourself haven't understood what the focus is on, you'll be presenting all sorts of stuff, and you'll waste time working on various things. And you can't always expect the stakeholders to come to the to your team, the data team, let's say, to give you the focus. I think you you definitely need to help. So I mean, that happens all the time and there's natural, there'll be natural conflicts. Like, I mean, a marketing team will say, I wanna, you know, they'll often are wanting a lot of reach, for example. And that is not necessarily gonna be the best ROI or or whatever it might be. I mean, those things can happen So regularly. So that makes sense. So then, like, part of the function of your team is to is to keep focus. Yeah. You bring that focus. Yeah. Make sure one of the problems are gonna drive the most revenue, the most impact, that you as a data team, you have the responsibility to make sure that that that you know what those things are. You're not just being told by people you never got. Brand. That that's at a junior level when you're dealing directly with your stakeholders. At my level, it's also, you know, should we be investing more in acquisition or in, you know, getting more PMs to work on churn reduction, whatever it might be. It's those trade offs and or, you know, should we build a new feature, or should we focus on quality of service or, you know, whatever it might. I mean, there's heaps of different things it could be, but, but but once you decide, you keep people focused on that, and and you also say, hey. This is how we're gonna measure it. And and then let's clarity. Let's talk about problem solving because the four things which I think is really interesting is that you I think one of the ways you've worked is that the way your team works, that you are seen as, like, the organ the place to go to get a problem solved, that you're there to think through problems. Like, how has that materialized? What is it that makes makes your team so good at that compared to other parts of the organization? Yeah. I mean, I think it depends on the problem at hand. But if it's a problem that I I that people think can be solved quantitatively, then, yes, it'll come to us. And sometimes we have to come in and and say, look. We we see that, you know, there's some inefficiency here. Let let us help and get to the bottom of it. Yeah. I think that you we've gotten the I mean, for I mean, maybe not everybody trusts us, but for those who do, the majority of the company outside, it's probably just from helping them in the past. So I think you probably have to start by kinda muscling in, doing a good job. Yeah. And then and then they'll come back. But you you've gotta be wary as well because they start coming back for things that you don't wanna be doing. You start to kind of you you don't want them to just start outsourcing all their work too. That can happen as well. But it that's helpful. It's a it's a virtuous cycle there. Right? If you do a good job and you help meaningfully, they will want more more help. And that's kind of the key thing. I mean, I think it's it's also org specific. If you're if you're say levels of, you know, for example, let's say there's a problem in a performance marketing team where, like, a channel's underperforming or something, or they're, like, just wanna know how can we better optimize our, investments. It's the same. I always like, oh, go speak to these guys, then they will. But if they're not, then, yeah, you kind of need to say, look. I'm seeing the results. I think we can do better. Let's sit together and work on it. And and it comes it flows out of that focus. So if you've said, this is your objective. This is what you need to improve this quarter, this half, this year. Then, you know, you need to draw up the the business owner needs to draw up a list of initiatives, and you wanna work with them on that. And they'll wanna work with you on it as well because they they they need to meet their objectives. So I think the problem solving flows out of the focus. And then, yeah, try and be helpful, and and that's how you win people's trust, I suppose. And then so, like, tell me so, obviously, this has been a journey for you to get to this kind of level of impact where you're where you where you where you describe yourself, like, you are looked at to help with focus. You're help you're you're looked at to help. Like, the the c suite is looking to a team to to lean in and make a big help of the team that move a lever. What are the skills that you're that you've been that you now as a team have that perhaps weren't there to start with or you now look for you bring in someone who hasn't been working this way before? Like, what's the skill set that you're you're a data analyst, but you're you've got the skills that we actually think works well in this team. I mean, we're we're kind of particular, I'd say, at least compared to the our peers in Paris and from from what I can tell. I mean, I might not. I don't know exactly, but we pretty much only hire out of university if we can. It's something that I actually have lots of arguments with, with the. I'm sure. Exec at the start of the guitar. My exec was always like the CRO was always, oh, we we need some more senior people. And I was like, no. Patience. Oh, sorry. So you mean, like, you hire very junior people from the back office? Hire the junior. So you essentially have a cycle of someone leaves at the top, everyone moves up, and then you hire at the bottom. Okay. So you you actually even sort of of you've actually come to realize you wanna you wanna train up from a very early Asian career rather than have bad habits built in up too late. Yeah. Yeah. Because, well, I mean, there's a bunch of re there's practical reasons for that. It's much cheaper to get someone who like the top one percent is the, well, this is just getting into kind of recruitment now, but the price, the salary difference between the best graduate and the worst graduate is much smaller than the salary difference between the best head of and the small head of, and the worst head of in in a market. So if you're really fighting over talent, you wanna fight early if you're if you don't have the biggest budget in town. But it also means you you can train people to work the way that you want. And, and it also means people know that they're gonna get promoted because they know that you work that way. So that's so when we're looking, we're looking at junior people who, I mean, I think the number one thing we look at I well, I look at, we have, like, quite a few rounds of different people. You you need, like, to pass a technical test, so I think it's that difficult. But you we we do kinda case studies that sees how quick you are at maths, how quick you are at kind of business concepts, pricing, mark changes in margin, things like that that make you think. Sometimes it say, you know, how would how would you run an AB test on a product? But this is kind of pen and paper sort of case studies. Okay. And it's looking for I mean, I'd say my experience, the people with the best of the numbers, following through, you know, what we're saying and then doing their little sums and going they've been the best, once they're in. And it doesn't matter if they're from in in France, you know, you've got a kinda split between engineering schools and business schools, and they're sort of culturally different. It doesn't really matter which one they're from. I've found that both can be really good. It is it sounds like it's about the the the ability to think, the ability to problem solve, to be logical, to sort of to just be Yeah. Yeah. There's always, like, a cultural aspect as well, like, for every team and anyone, obviously. But for, yeah, those the skills that we look for, it's nothing special. It's kind of ability to think I mean, you might call it intelligence, but, you know, it's not exactly that. Whatever it is, it's yeah. That makes sense. I mean, ultimately, great talent is gonna lead to great results. That's a very that's obviously a very important part of it. And then make get that feedback loop. I've got, I I'm conscious of time. We've got so much to talk about. All things I wanted to get to was a question that someone from the community gave me to ask you this as we talked about how to become more the problem solving function. And I think this is really appropriate is they they said, I buy into data analysts being the organization's problem solvers, but what's the single best first step that our team could take to stop being seen as a dashboard factory? If you got anything, you you obviously been on a journey. It's not come quickly. I think that's one of the things you've already said. But, like, what would be the single best step that you could imagine that that you took or you that you took early on that you think others could apply if they're already in a kind of more of a support function mode of operation? I'd probably concentrate on your on the team and and the team's skills and, and the culture of the team. So I think what I focused on first, and it was, you know, because I'd moved from, a non data, you know, very business focused role, I've I've kind of brought that to the team. And I think that's the first step. So understand the p and l of your business as better than anybody in the company, then which you might be like, why would I do that on a day round? Let's just do it. Then, understand how each team impacts the p and l. And then I I think when you're then having conversations with them about their business, you're bringing that in the background. And that's gonna kind of be the first step, I think. You that's a great so you could make sense. I don't know. Yeah. No. I I you're basically I think if I just tease out more, you're saying it's great advice. You're saying if you know the business well, you can have impact. You can have credibility. You can actually start I think it's just it's just because the you'll change yourself. So the way you're having that conversation is gonna change. Instead of being like, yeah. I can build that dashboard for you. Be like, yeah. I can build that dashboard board for you, but, you know, what about this? How are you impacting this? Do you need to do this? Because you you understand what the how they impact the business, and you'll and you'll you wanna bring that, three hundred sixty degree or whatever view Yeah. Because you're working with all the stakeholders. And and you're coming to a table with an opinion. You're not just saying, what do you want me to do? You're saying Yeah. Yeah. Yeah. I'll have an opinion on this. I actually I'm not just here to press keys. I actually have an opinion about this business. I understand this business works too, and therefore, I think we should look at it this way. At least then you've started to problem solve with them. You're giving them alternative viewpoint. Yeah. Yeah. I mean, an example, Adi, and if you go back to the four tenants, I mean, this doesn't happen all the time, but I'm sure everyone's had this experience with, like, a PM that wants to build a new feature because it's really cool and fun, but we'll have absolutely no impact on the business. And you might be like, that's cool, but, you know, we see from x y zed, it's not gonna increase retention or it's it's not gonna increase engagement. Engagements correlated to, retention, which is, you know, obviously lifetime value, which is where we get our revenue from. So why don't we focus on something else? Like, this is probably a better thing to focus on. Or, you know, I don't know. It's a made up example, but something like that. And then so you're bringing bad ideas. So I think the first step would be to know it yourself. So and then it'll come naturally, I'd say. I I can that makes total sense. You're coming in with an opinion. You are the bit the mental step, I think, we're describing is I'm going to this business myself. I'm gonna have an opinion about how it works and where we got how to solve problems. What's driving revenue? What drives costs? Exactly. And as you go, as you get more knowledge, as you solve problems, you retain that knowledge, you go back into the business, you have more evidence, more data led evidence to help you be better at that at that task and be more useful. Yeah. That's that's really great advice. That's awesome. Tivo, we're almost at the end. I'm so grateful for your time today. If you wanna find out more from Tivo, he well, you can find out find him through our show notes. You can go to cal dot co slash, n t n, where you can find all the episodes as well we've had in this series. Tivo, I'm so grateful for your time. Thank you for taking time out of your day to come speak to us and tell us about this transformation. We've learned about, what it means to change to get a business performance rather than just dates. We've learned about problem solving, recruitment. We've covered lots of different areas. I'm grateful to you for that. Thank you very much. Thank you. Hope it's been useful. It's been great.