Today, Betsy is speaking with Jonathan Fianu, Director of Global Revenue Operations and Business Development at ComplyAdvantage. Join us as Jonathan shares insights from his unique career journey, from entrepreneur to sales leader to RevOps executive. Betsy and Jonathan also discuss key RevOps topics like architecting flexible teams, establishing data benchmarks, and leveraging AI.

Guest Bio: Jonathan Fianu is the Director of Global Revenue Operations and Business Development at ComplyAdvantage, which provides anti-money laundering technology. Founded in 2014, ComplyAdvantage is Regulation Technology (RegTech) organization that “uses artificial intelligence, machine learning, and natural language processing to help regulated organizations manage risk obligations and counteract financial crime.”

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Announcer: Welcome to another episode of The RevTech Revolution. Today, Betsy is speaking with Jonathan Fianu, director of Global Revenue operations and Business development at Comply Advantage. Join us as Jonathan shares insights from his unique career journey from entrepreneur to sales leader to Rev Ops executive. Betsy and Jonathan also discuss key Rev Ops topics like architecting, flexible teams, establishing data benchmarks and leveraging AI. Let’s dive right in on the RevTech revolution.  

Betsy Peters: Jonathan, thank you so much for making time and joining us here at The RevTech Revolution. It is spectacular to see you. Happy Friday and welcome.  

Jonathan Fianu: Happy Friday to you, Betsy. Thank you for having me. Delighted to be here.  

Betsy Peters: Wonderful. Well, let’s start off by having you do a little bit of an introduction to the audience about you and your journey into revenue operations.  

Jonathan Fianu: Yeah, absolutely. And look, I think for myself, it’s been very much of an atypical path. If I go way back, I was actually an entrepreneur for many years after university, doing all sorts of different things. Betsy I think we’ll need another podcast to really dig into it, but what I really took from that journey was my love of selling and love of the commercial part of building a business. And I thought, look, let me just start at the foundation and build up from there. So I went and became a business development representative, a BDR or SDR as it’s termed, did that for 18 months, then became an Enterprise Ae and then a sales director. And so I had a big part of my journey. One of the big stepping stones was being a sales professional. And I do think that does have a real advantage.  

When you start to look at revenue operations, you can come at it from different angles, but that stepping stone I found was really key for me. And then from there, well, whilst I was a sales professional and going through that journey, I was constantly aligned to different systems. So I was in charge of the CRM as well as selling, but also the person in charge of helping to structure it and admin on it. As I sort of progressed from Enterprise Ae to sales director, I became more involved in the handover process between marketing and sales and CS. And so I was already close to revenue operations whilst I was in that period. And then I had the opportunity to really just focus in on it at Comply Advantage. So a rapidly growing scale up headquartered in London, but with bases in New York and also Singapore, and they wanted someone who had been a sales professional before and who wanted to take that next step into revenue operations.  

And so I’ve been doing that now for the last three years. I absolutely love it. It’s a massive passion area for me and we’ve seen economic growth in the business and I’ve been able to understand how that Rev Ops vision can be put into place in a high growth company. But in sort of recap, I’d say there’s an entrepreneurial journey which kind of led with the creativity part of things and then the sales professional journey from BDR to sales director and then starting off and building out the revenue operations team. 

Betsy Peters: There’s so much to dive into there. So let me ask a couple of questions about all that.  

Jonathan Fianu: Sure.  

Betsy Peters: So, in terms of your entrepreneurial journey and your sales journey before you got into Rev ops, what are a couple of the pain points that drove you more towards process and or technology or even data? What about what you experienced in those first two parts of your career pushed you towards this as the kind of culmination or at least the current culmination of where you are?  

Jonathan Fianu: That’s a really great question, betsy and I would frame it like this. When I was an entrepreneur, one of the key challenges was around a CRM or database that could really suit the needs of literally a sort of one two man, three man band trying to flex and pivot and bring a product to market. And so that was a key challenge for me alongside data and how to even tackle the go to market motion when you’re having to do that, alongside looking at your marketing spend, alongside trying to speak to investors and so on. So there was a real picture of.  

Betsy Peters: Payroll goes out, all that.  

Jonathan Fianu: Yes, exactly. So there was a real systems challenge there. When I was a sales professional, CRMs had already kind of really taken off quite considerably by that point. Salesforce was still a key CRM in the ecosystem, but there was other players around that were Vying, Sugar, CRM and so on and so forth. And so that was okay. It was then more process, it was how to leverage data in the process and handover and how does the data flow from team to team. That was a very nascent area at the time. A lot of CROs were kind of shooting from the hip. Right. I think this I’ve experienced that without really thinking about data and how it flowed through. And so that was a challenge that I experienced in my sales professional journey. And it was some of those experiences that I took to comply advantage at the start when we set up the function, it was a case of, well look, let’s try and do things a little bit differently.  

How do we actually set it up to scale? How do we start to think about data systems and processes, the foundation before then moving?  

Betsy Peters: It sounds like the folks you work with now in terms of the way they structured your job description were very aligned with us in the way we think, which is data first, right. And experience first. So somebody who’s experienced all those pain points and then have them design the systems and really optimize for what can.  

Jonathan Fianu: Be, you’re spot on there, Betsy. And it’s also empathy. It’s really understanding your stakeholders right, their pain points, right. When you don’t have that perspective, then it kind of feels a little bit alien when you’re asking your stakeholders to either adopt something or when you’re looking at the enablement for a particular process, it’s like, why can’t you just do it? But the reality is that the sales professionals, it’s a different motion, different mindset, they’ve got different tasks to do and systems and data should be there to support and enable. So I think the empathy piece is also a big part of it.  

Betsy Peters: I agree, for sure. And just understanding alignment of what people’s goals are and who’s going to put data in because it’s aligned with their goals and who wouldn’t because it’s not right. So just simple things like that only a true sales professional or marketer might understand.  

Jonathan Fianu: Exactly. I think any exposure to parts of that commercial journey, marketing, sales, CS, that’s a benefit, right? Because then you can bring that to how you start to think about deploying the system, how you start to think about the pain points and challenges around the processes and data in those respective areas.  

Betsy Peters: Yeah, absolutely. Before we get too deep in your current situation, tell us a little bit about the revenue technology that you’re currently using. And particularly, what could you not live without.  

Jonathan Fianu: Thinking about this look, so for me, the CRM is for me, it sits at the heart of the stack. The CRM is evolving and changing and we see that with some of the different acquisitions that have happened in the space and also the range of revenue tech that’s around the CRM. Now, in terms of how sales professionals start to interact outside of it, but data sits within it. So the CRM for me is one of the pieces you can’t really live without. But if I was to look at the commercial technology stack and break it into three pieces, lead gen, sales execution and then post sale so in terms of the lead gen side, we use a bunch of data providers zoom, Info, Cognizant, Lucia I tell you Betsy, I really wish I had them when I was setlinks. It was much harder before. So at least one of those providers, cognizant I’m a big fan of.  

So one of those data providers within the lead gen stack I think is key. We have a bunch of automation which then sources accounts and contacts and enriches those. We can dig into that a little bit later and brings that into the CRM. And then when we start to look at the sales execution side of things, it’s everything from using Sequences and sales engagement platforms, outreach and lead routing as well. And the marketing automation, we use HubSpot and then flowing through to the Conversational Intelligence piece. There’s big players here. One of my favorite is Gong. I think they’re a fantastic CI tool. And then you have other tools that we use, like clarity forecasting and then post sale, we look at churn zero. I’d say the CRM for me, salesforce is one of the key CRMs that I probably either can’t live without or you need to have some kind of CRM that’s there.

Cognizant on the lead. Gen. Big fan of Gong. So I’ve mentioned a few there, Betsy, but it’s really hard for me to split it out, just having been so close to it.  

Betsy Peters: Yeah, no, and I appreciate that you’re dealing with, depending on how you characterize this, both sides of the bow tie. Right. There’s the prospecting and there’s the actual sales execution, like you said, and then there’s everything that happens to keep and grow a customer. So, yeah, the rev tech space has exploded, as we all know, and it’s interesting to watch the specialization in different areas of that journey and the consolidation in different areas of that journey as well.  

Jonathan Fianu: I think this is one of the most exciting periods for revenue technology at the moment. Not only are we seeing, as you say, that specialization and a real understanding of how each of these tools provide value across the stack, but then we’re seeing the advent of generative AI and it’s like you mash the two of those together and suddenly it’s very exciting indeed. Right. You can start to leverage and get real power and insight to drive a business. So, yeah, I think it’s hugely exciting. Equally, as you share, there’s consolidation, there’s this wider market to rationalize your stack because of cost, because of efficiency, and.  

Betsy Peters: Tell us a little bit about the composition of your team, who helps you connect all of these platforms and data and make sure it all comes together. What does your team look like?  

Jonathan Fianu: Yeah, so we have analyst structure, and the analysts would be paired with and aligned to the different departments sales, Marketing, and Customer Success. So we have three analysts and then we also have a systems administrator. And so the system administrator would be that partner between all of that tech and our stakeholders and the technology’s customer success team. Right. So my colleague Ollie, he’ll be there to understand how outreach works in detail so that he can triage and work on issues ahead of time and only route the most essential stuff over to the outreach team. And then my colleagues Samina, Evelyn and Maya then support the wider stack. And the reality is, Betsy, we’ve evolved as a team. So previously we had marketing Ops and CS ops within the revenue operations function. Now those have actually split out and gone into those respective areas equally. Salesforce has got us now its own squad, so it’s now got its own separate, dedicated squad, just given the way the stack and the estate has grown.  

And so what I’ve found is that revenue operations evolves according to the maturity of the organization. And it’s been fascinating to watch.  

Betsy Peters: So how would you characterize the revenue operations team itself at the moment? Are you really more about the intelligence or more about the systems or how would you characterize that dichotomy?  

Jonathan Fianu: Great question. I’d say it’s primarily now. Sales, ops and insight. If I was to kind of like strictly categorize it, the revenue operations team still liaises with our partners agatha in the CS Ops team and Mark and Jack in the marketing team, but they have their own respective teams that they now work within. So, yes, primarily sales, ops and Insight. And I think the Insight piece is an area which I’ve really enjoyed seeing thrive and grow within our business, from having no reporting at a high level to now having just copious amounts of reporting. So it has its own challenges.  

Betsy Peters: Right. What do you watch and what do you pay attention to?  

Jonathan Fianu: Sure, exactly. But it’s been fascinating to watch that evolve.  

Betsy Peters: What were the indicators that you needed to change from being more central to being more dispersed and specialized in Sales Ops and Intelligence?  

Jonathan Fianu: That’s a really great question and it’s something that I spent alongside our CRO a good couple of months at the beginning, just thinking about how are we going to architect the revenue operations team for the size right now, but also for the scale journey that we had in mind. And we had to set up several guiding principles, so to speak. Right, so I guess to frame this, I’d share my understanding of revenue operations, which is there’s a target that the CRO or CFO holds. You have various levers which affect that target revenue generation, revenue protection, revenue growth. And then you have the commercial function which sits underneath. And each of these different departments have different effects on those levers. Within each of those departments you have systems, data and processes. And so Rev Ops is there to harmonize and optimize the systems, data and processes across that commercial function.  

So we started from that perspective and said, okay, at this moment when we started out, we needed to have analysts which were fungible. They needed to be able to work across the commercial team because we still were trying to find out exactly what were the core challenges and issues to focus on. And so at the start we had analysts which was 70% aligned to Sales, but still had 30% capacity that could work across marketing and the CS team. And the capability was reporting. And so reporting was needed across. And so this was one of the perspectives that we had. The other was another principle or position that we held was you can separate functional and strategic leadership. And this was a really important linchpin in how we deployed and scaled. So the idea was you could have functional leadership day to day around the role and then you could have leadership around specific initiatives.  

And that leadership could be that can come from someone else. And so at the start when the traditional sales ops, marketing ops and CSO ops structures started to form, as an example, the CS ops would be reporting into me and also taking strategic guidance. And then as the CS team evolved, she would then take strategic guidance from the CS ops leader but functional guidance from me. And then over time, she would then split and have functional and strategic guidance directly within the CS team. And so we had to have certain positions, we had to have certain principles and approaches and then were just responding to the data and the growth of the business as went along.  

Betsy Peters: Sounds really smart. How did you come up with this roadmap?  

Jonathan Fianu: I can’t take all the credit here. So this was in partnership with our CRO. This was listening to the different stakeholders across the business. This was listening to different team members who then joined as well and brought in their influence. It’s something that evolved over time. But we started from a position which was we’re not going to go with the status quo from the set. We’re going to put in something that is flexible and adapt as we go along.  

Betsy Peters: Yeah, smart.  

Jonathan Fianu: That’s great.  

Betsy Peters: Anything you do differently based on where you are now.  

Jonathan Fianu: Yeah, I mean, look, there was a ton of learnings throughout all stages of this, right? So working around like in order to make this work, you need to create different, what we call mission based squats around problems that are typically across different departments. And so the journey to that is the journey of learning is quite long when you’re starting out and you have no real sort of framework. And let me explain that. Which means we had to kind of understand our benchmarks and we had to look at where were trying to progress to and look at the different stages, but we didn’t think about how we could template that whole approach out from initiative to initiative. So each initiative we would start right from the very beginning all over.  

Betsy Peters: Yeah.  

Jonathan Fianu: And it was a very arduous process. We didn’t move as fast as we could have. I think looking at automation sooner, perhaps. I think automation is a great way to address scale challenges and so yeah, that’s another learning that we kind of took a little bit later on in the process. So there was learnings like that we had to kind of take on board.  

Betsy Peters: Thank you so much for sharing all that. It’s the details that I think mean a lot to the listeners because in the past we have terrific guests and we’ll talk strategically. But actually getting down into organizational structure and the way it morphs over time is certainly unique to culture. But I think you’ve given a nice schematic that would be great to see on the back of a napkin somewhere, but also a good evolution of where you’ve come from. I want to shift just a little now into data, maybe again with that same lens of where did you start and where are you now? What were the biggest challenges for you when it came to data?  

Jonathan Fianu: Yeah, so this is genuinely one of my favorite areas and topics, right? My CRO posed a challenge when I first joined. He’s like, look, how do we increase quantity and increase quality at the same time? And yet, traditionally, this is like a seesaw, right? You know this Betsy. It’s like, hey, if you want to bring in a whole load of data, yeah, great. But then when you test it, track it, make a call, send an email, it’s like, okay, this data is not great. And then if you want to get really tight on the quality, put in a ton of gates. Well, you can’t move very fast, and the pool is small. So the question was, how can we do both? It was almost a stubborn question, like, no, I don’t accept that this seesaw is the only way forward. There’s got to be another way.  

And again, thinking in the same principle around, okay, what’s our guiding point or principle or position on this? We came to this understanding, which is the minute a data point is in, your system is technically out of date. It’s a kind of like Schrodinger’s cat kind of idea, right. Until you a data points in your system, but until you actually make a call, send an email, actually check if that person is still at the business, or you have a system in order to do so, you think it’s correct. It is technically correct until you actually perform an action, you find actually it’s not.  

Betsy Peters: Yeah, it’s inert. Yeah, exactly.  

Jonathan Fianu: So we work from that position. And so we then broke down the core workflows. In essence, data for us, and I think for most businesses, and supporting the sales function is accounts, contacts, opportunities, right? It’s companies that you want to talk to, it’s people that you want to engage with. So we broke down four core workflows account sourcing. So finding new companies, account enrichment, right? Finding the LinkedIn, the size, the location, finding new people. So finding new contacts, and then contact enrichment as well. So new email and a new phone number. So four core workflows. And we understood that our position here was that you’d have to be in this constant state of enrichment. So the first thing that we did was really just set our benchmarks, which Betsy was not. Now it sounds even as I’m saying it sounds easy. Like, okay, we’ll just find out how many contacts and accounts you have.  

That’s very difficult when you inherit a database of unknown quality. It’s like, I haven’t been in a business where the CRM is clean. Everything is exactly as I expect it to be ever.  

Betsy Peters: Yeah, it’s like buying an old house, right? You walk into the old house and you’re like, oh, this is lovely. And then all of a sudden, you open up a cupboard and you’re like, oh, okay, I got to fix that. Okay, I got to fix that. Yeah, the domino effect.  

Jonathan Fianu: Exactly. So it was like just getting to the journey of understanding what is our accounts and contacts was, like, super important. And we did it by splitting into quantity and quality. And we chose quantity first. It’s the easiest one, right? Okay, let tell me how many accounts that you have within your Target segment that have had these particular fields or attributes filled in. Just count them for me. So the quantity side was easier, and we kind of got into a rhythm of just trying to understand that. And then we had to define what the quality side was, and that was like, okay, how are you going to define what a high quality contact is? What is a high quality account? And so that was a super fascinating journey in understanding. Well, what attributes do you want to track? How do you start to break those down?  

So for us on the contact side, it was okay emails. It was checking for certain bounces. It was bringing a phone number in. It was making sure there was feedback loops from all the systems to tell if there was a bounce, et cetera, or a do not call or a wrong number. We had that whole kind of piece in there. And then for accounts, we said, well, a high quality account was a contact. That was a high quality contact within the persona that we actually wanted to target.  

Betsy Peters: Yeah. And how did Engagement play in here? It sounds like you have a lot of kind of static stuff. You’re actually talking about a lot of closed loops. But were you also using engagement as a guide or how did that work?  

Jonathan Fianu: The team was using outreach as our sales engagement platform, and so that would feed into salesforce and into our data pool again, that would in turn feed our different reports. But even that is not straightforward, Betsy. An example is, oh, outreach has said that it has bounced. Right. Legitimately said that it has bounced. And then you check it with another system and you find, oh, actually it didn’t bounce. It was actually fine. Okay, so maybe it’s now domain reputation. Maybe it’s in a catch all. So we had to uncover these little nuances with the data, which you just don’t see or don’t understand when you first look at it. It was an evolving piece there.  

Betsy Peters: Yeah. Interesting. And how long did this part of the journey take you?  

Jonathan Fianu: It took us around 18 months to get right, to really get to the point where we’re like, here’s what a quantity metric looks like. Here’s what a quality metric looks like. I can tell you definitively how many accounts and contacts within Target meet that criteria, and I can tell you which systems powered individual attributes of it and how those are performing over time. Yeah, that’s an 18 month, two year journey, betsy yeah.  

Betsy Peters: And how do you get the teams that are working on it during that 18 month journey to come along? Because of course they’re ready for the end state yesterday. So how do you get the time to go through? Because I love the kind of principles, first approach it sounds like you’re taking and you’re doing a very thorough job here, but you’ve got the day to day scrum of all these people using the system and cranky with you. So how do you balance all that?  

Jonathan Fianu: Yeah, so the first piece was setting expectations with the leadership within each of those teams to say, okay, look, we’re going to go on this journey, we’re going to be super communicative around how we’re progressing towards it. But you need to understand that it’s not going to be like, click, tomorrow data is great, there’s going to be angst, we’re going to get some things wrong, we’re going to be doing a test, learn iterate approach, and by definition, some things may not work. So the first bit was like huge amount of expectation setting. Then it was halted communication. And that communication isn’t just in, oh, let’s have a meeting, it’s, here are our OKRs, here’s the metrics, here’s how the benchmarks are trending so everyone can see it, everyone can access it. And so expectation management, communication, those were two kind of core pillars. And then it was constantly going back to our core stakeholders.  

So we would go back every time we’d get a request for an enrichment or for a new account sourcing, maybe for a go to market initiative, we would go back to that stakeholder. Even though we’re seeing certain information in the data, we’d say, okay, we’d love to get your feedback as to what was going on. And that was like, fascinating. We would get data from our databases and we would see certain segments and were like, great, we’ve done our job. You asked for this segment, it’s in that segment. Here we go. And then the stakeholder like, sales leader will be like, this is rubbish, these are clearly not fintechs or these are clearly not et cetera. And so you’d have to go back. And that was when we started to build little fixes such as, okay, always look at the description along as the website, look at the other fields alongside the data extract, see if those actually tie up.  

So that was part of the journey and yeah, I thanked the team for their patience because it was a long journey.  

Betsy Peters: And as you were doing those types of projects, it sounds like you were also extrapolating the learnings from that across all the other things. Right. So if there was a particular segment and go to market that you were finding all these things out, then you obviously were able to benefit across the whole platform. And put those rules into place. And the other stakeholders benefited from the projects that were in current in real.  

Jonathan Fianu: Not even it was a two way street. Betsy because were also learning from others in the business. So comply advantage is a financial crime scale up. We essentially take in sanctions data, politically exposed persons data, negative news or adverse media, and we bring in all that data and we work with different financial parties and financial institutions to make sure they’re not working with bad actors. But the actual work within there is super interesting. Like, the teams are looking at fuzzy logic, right? Is this name similar to this other name? How many characters different can we tolerate, right? So were working with those teams and saying, okay, cool, what can you tell us around how you’re looking at data? And we start to feed that into ourselves.  

Betsy Peters: Yeah, that’s cool. Working in a data business to get that feedback loop and improve what you’re doing, that’s terrific. Let’s go to something you mentioned earlier, which is Generative AI. So tell me how you guys are thinking about that. How are you integrating that into what you do every day? And then I have some follow ons after that.  

Jonathan Fianu: Betsy I think this is just a huge area. I mean, it goes without saying, but I know some people are apprehensive, some people are scared, right? And some people may not immediately see the value, and the reality is they’re all right. We are all right. There’s huge potential, there’s also a huge risk. It doesn’t also solve all the problems. Right. However, I do think it’s like a seismic shift. So my encouragement is like, lean in. So, I’ll be honest, I was late to the party. I mean, I think I’m still relatively early, but I was late to it. When Dali first came out, sort of image the image side of it, I was like, what is this? Quite understanding. Then ChatGPT came out like, wow, okay, people are really talking about this thing. Let me give it a go. And you just have to try it a few times and you’re just like, this thing is absolute fire.  

What is this? This is amazing. So, the first thing we did is we used it in our prospecting and just for refinement, doing some kind of cool things like, you’d take a LinkedIn profile, you’d take some key points, you’d get an icebreaker on the back of it, use that as a way to speak to different prospects. And that was kind of a fun way of using it at the moment. I’ve seen now different solutions tackling within the revenue space that are hugely exciting. So that’s beyond what we’re using at the moment. They’re just more things that I’m seeing. But everything from just simply typing in what you’d like to see and it being connected to your sales data all the way through to companies which are. Connecting to your resource hub and you ask a question and it’s then forming the correct answer. So no more of these, like, hey on Slack, hey, can you help me with this thing and that’s.  

Like the millionth time that someone’s asked that question. There’s some really cool stuff happening, but for ourselves we’ve just been using it in prospecting. But I’ve been encouraging the teams like lean in, lean in.  

Betsy Peters: Yeah, I was just going to ask you that because I think it’s obviously a full contact sport, right? And what we’ve been doing in experimentation is a lot of the copy stuff, but the hallucinations have slowed people down. So I think the first time they get kind of a negative experience, they’re like, it doesn’t help. So it’ll be interesting to watch this evolution of people’s understanding of what it’s good for and what it’s not and when to use it. But what we’re hearing a lot about across the ecosystem, salesforce included, is this idea of next best action and how can both automation and large language models be used to start offering up analysis of where things are and what should be done next, so that ostensibly efficiency goes up for the salesperson. So any experience with that yet or any thoughts about that direction the market’s headed or the hype cycle of all of that?  

Jonathan Fianu: I think it’s fully I’m fully with it and I’d say I’ve seen maybe three companies, interestingly enough, in completely different areas. So one company from Israel, one company in the US, one company in London, all tackling and describing doing what you’ve just described, or at least starting to build a product which would do that. However, the vision, I think that will play out in the future is one where the next best action is inferred and shared proactively without your input or requirement, like your sort of prompting it’s simply saying, I’ve been looking at your data, I understand your company, it’s within this particular cohort of others. I’m looking at different metrics which you typically track. I can see that this is a lagging indicator, this is a leading indicator for a certain problem. Here’s a suggestion on the root cause that others have provided. This will all be given directly to you as you wake up in the morning.  

It’s like go after these five things to either protect, increase or defend your revenue and your position. So I think that’s where it’s all headed. I think there is a journey though, to it. Part of the journey is data security, right? People don’t want to just put all of their data into one of these systems. I’ve seen some smart ways of getting around it, right, in terms of only holding it for a certain period, only sharing like snippets, the key, snippets that are needed, deleting afterwards, et cetera. So that’s not insurmountable, but it is an issue. The next piece is thinking about how to deal with the sort of time series issue in terms of tracking over time. A lot of the forecasting solutions out have kind of cracked that by just taking shots of every single action on every single data point. But unless you have that looking, historically is going to be really tricky.  

And then there’s the piece around. Just how do you start to synthesize the right action? Based on the metrics and based on what you’re seeing, there’s almost like a sort of revenue layer that needs to be built in, that says when this metric goes up, this metric goes down, it means this, and these are the factors that typically drive it. That’s not something that I think the system just would automatically know. It will know once you’ve told it. So I think there’s a few hurdles, but we’re going at like lightning pace here.  

Betsy Peters: Yeah. Are you finding going back to your point about the unique business that you’re in and the product side, are they already experimenting with these types of large language models, identifying patterns and starting to make recommendations? Yeah. So that’ll be interesting to see what you can apply.  

Jonathan Fianu: Exactly. And that’s what makes the whole it’s going to be transforming all industries. Okay. Not all, but a large many industries, Betsy, ours included, and we’re starting to see it already.  

Betsy Peters: How much do you worry about the underlying data and its quality and veracity to actually feed into those things that are starting to make it sounds like you’ve got things down because of the 18 months you’ve spent there. But maybe on a scale of one to ten, how much is data quality a worry for you as we get into this world?  

Jonathan Fianu: It’s a big worry, and I’d say probably a seven. Right. That seems high, given the effort that we put in. But working on that same principle, all of our motions, our actions could also be technically out of date. Right. There’s new approaches that can be taken. The data sources or databases that you use that you relied upon that were great, suddenly they depreciate. So it’s always going to be like a hot button piece for me. Betsy, you just hit it on the nail, which is garbage in, garbage out. Right. If the underlying data is not great or if your sales data is messy, then you’re not going to be able to infer or glean the right answers or the right insight. So this is something that I think everyone needs to be really thinking about right from the very beginning. And I remember when I joined Comply Advantage, one of the first projects that I was tasked with was the Configure Price Pop CPQ, because it was like, you know what, we need to have guardrails on the data.  

We need to understand contracted data. We need to have that utilization. We need it to be in a workable form in order for us to really run in the future. And so this is the thing I’d encourage everyone to really think about the data quality, how to make sure any investments that you make in streamlining it, in, improving it, are going to be worth it.  

Betsy Peters: And how much of that is human organizational structure versus automations and processes you’re layering on. Like, what’s your sense of that at the moment?  

Jonathan Fianu: So I think at the beginning it’s the organization, right? You need to bring this data first mindset to the business, the very beginning, or else no one’s really going to be motivated to do much or they’re going to be tolerating something which they really shouldn’t. So at start it’s really having that data mindset. But then after that, you need to start to think about what the automation journey looks like and how to deploy it. And one of the drivers for us, when were looking at the lead gen side and automation there was selfishly, just cost. We’re like, okay, you have a sales team that’s 25 people, that grows to 50 people. We’re just going to have, what, like 50 licenses now? We’re going to have just like 100 licenses now. It’s like, how do you start to build the automation so that you can be more efficient with your, spend more efficient with how you deal with different errors, right?  

You’re spending less time on those because things are being sorted in these loops. So I think it starts off with having that organizational piece, but then it very quickly. Well, I think any automation that you also want to bring in, it comes at a cost. And again, you got to make that case, which we had to make the case to our CFO, and it was like, we want to invest in this area. So it kind of goes back. You can’t really make progress if your execs are not bought into what it means.  

Betsy Peters: And I can see your Rev Ops team and your execs getting bought in, right? How do you get the sales team bought in? Because there’s that I’m looking at the data, I don’t trust the data, so therefore I don’t invest in the data. And how do you change that so that they are data first and really helping with the transparency and the quality themselves?  

Jonathan Fianu: We started off with something really fundamental here, Betsy. It was just why is it important for the data? You think about a sales professor, they’re going about their busy day, they go to the CRM, they see like 50 fields, they’re like, I don’t even know what this one’s used for, right? Why do I need to fill that one in? If you don’t explain why different fields and data is needed for different things, no one knows. And a great example is we changed the closed lost pick list and we said, look team, we want you to fill it out, do a little bit more. And some people are just like, I change it. It’s okay. I’m like, it’s not okay. We got to explain and share marketing spend a ton of money bringing these leads in. You then qualify them, right? If you don’t tell marketing why you’ve disqualified or get granular enough, well, that stuff’s going to keep on coming, right?  

So you want it to be more effective, you want more of the good stuff. Suddenly people are like, all right, okay, I’m bought into doing these two or three more clicks. So it starts off with why, and then it’s really pairing that with enablement and also holding your hands up when it’s gone wrong. When you put in something which actually is too onerous or unnecessary or major pushback, it’s like, okay, we got that wrong, we’re sorry. And being able to just walk back builds that trust and credibility. People then understand, okay, we’re all in this journey together. We understand why it’s happening, and then we appreciate that it can get changed if we voice reasonable opinions and feedback around.  

Betsy Peters: Yeah. I think this is another case where your history gives you the empathy to be able to have these communications that are well received, right? Because sometimes it’s all in the way you say it as you know it. Right? So I’ve been on the receiving end of a well meaning It team who doesn’t have the empathy, trying to enable, and it’s a very different situation on the other end of that communication. I think that’s another kudos to your bosses for picking someone who was in it and understands it and can communicate like that. That’s great. Tell me what you’d say to someone who’s young, who’s interested in getting into this field. It’s the fastest growing job description on LinkedIn right now, and lots of people from sales, but also It and even marketing are interested in the space. So what do you tell people when they ask you about the career path and what do you do first type of thing?  

Jonathan Fianu: Yeah, that’s a great question, Betsy. I think I’ll start by sharing that we are super fortunate that as of this moment, there is a huge free university out there, right? There are people, there are peers, there are leaders in this space who are constantly putting out content on LinkedIn, podcasts, books, different frameworks, right? Winning by Design puts out like, a ton of great content in this area as well. And there’s individual leaders who are super vocal and super sharing, right? They’re constantly sharing. So the first thing I’d say is, like, look, there’s a ton of great leaders in this space. Seek them out. Seek and see who’s actually doing revenue operations industries that you’re passionate about and interested in. You’ll find that they’ve got content. They’ll share challenges. Like, a smart person learns from their mistakes, but a wise person learns from others mistakes. See what they’ve gone through.  

So that’s the first thing. The next thing I’d share is, look, I think the role is very it’s got a numerical, it’s got analytical sort of foundation. So any kind of courses and so on in those areas I think is helpful. I think there’s also a ton of courses as well. I think Pavilion has its own Revenue Operations certificate. I think it’s in partnership with Winning by Design. So you can understand forensically, how do you actually put together these different concepts and how do they work. However, that’s like theory side of it. You got to also look at the practical. And the practical is, if you’re not already in the role, I would look at opportunities to understand the systems that you have in your business, the data flows that you have in your business and the processes that you have. Even just speaking to different individuals who are responsible for those areas and trying to understand how it works.  

Even just putting together your own schematic as your own understanding, you start to be on that journey of actually, what is rev ops. And then really it’s then up to all of us in the industry and in this space to give the opportunity to others who are super interested and also have a passion for it or have the aptitude that we can see for it. To help guide to share our time. I’m constantly having little 30 minutes chats here and there with different people. I love it. I learn a ton. Right. And then also it’s a way to give back and give the perspective. So I think there’s a bunch of areas there, but we’re super fortunate that as of now, there’s just so much great content that’s being produced.  

Betsy Peters: No question. Any first principles in this area that you use when hiring for people?  

Jonathan Fianu: Because I came through an Atypical path, I’m kind of like I’ve got wide open for the atypical. Great. Someone which is very different, but also interested in the area. Yeah. I’m going to give a full look in right. Because I understand you can come in from all quarters. However, I am looking for that base of analytic or numerical sort of foundation. Right. Because I think that’s super important. When you start to think about data, information flows, metrics, there’s got to be some kind of understanding around it. The kind of familiarity and exposure to different systems or different departments which sit around or within the Revenue Operations kind of sphere. But to be honest, Betsy, I try and keep an open mind. Right. I think anyone could be interested in this area and this area has people from all backgrounds.  

Betsy Peters: Yeah, that’s terrific. And I think that’s, again, going back to your empathy point, it only helps because it’s the entire customer journey you’re supporting with data and technology and processes. Yeah, absolutely. Anything that we didn’t ask that you think would be helpful to other Rev Ops practitioners?  

Jonathan Fianu: I’m not too sure. I think we’ve had a really wide ranging discussion.  

Betsy Peters: Yeah.  

Jonathan Fianu: You’ve been terrified on all of these areas, Betsy? Well, you know what? There’s a piece which I think is just kind of tangential or to your last point, which is just on diversity. I think having more diversity within the space will be great. I think within sales in general, I think it’s super important. I think that starts with it starts with the managers, it starts with the company, it starts with even just your messaging in the job description. These things are little ways that you either encourage or discourage, either promote or attract or push away different people that I think would be great for not only revenue operations, but sales in general. But yeah, that’s the only piece I kind of add. Betsy, I think we’ve had a really great discussion. I’ve really enjoyed it.  

Betsy Peters: Me too. Thank you so much. It’s been really fun and great Friday into the weekend conversation.  

Jonathan Fianu: Absolutely.  

Betsy Peters: What a terrific one, and we look forward to crossing paths with you again.  

Jonathan Fianu: Awesome. Thanks, Betsy. Thanks for having me.  

Betsy Peters: Thank you, Johnny.  

Jonathan Fianu: Cheers.  

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