Sean Lane 0:12
Hey everyone, welcome to operations, the show where we look under the hood of companies in hypergrowth. My name is Sean lane. for a certain period of time in start up land mantras like move fast and break things or do things that don't scale, rule the day. And it makes sense they make for great marketing taglines. Take the discipline, thoughtful approach doesn't really pop off the wall next to your ping pong table. But the funny thing about discipline is that it takes discipline. It's hard moving fast is easier. As someone who tends to move pretty fast, I was grateful to be challenged by this week's guest, someone whose discipline I really admire. That guest is Rupert Dallas, VP of revenue operations. At audio I an accessibility platform that helps businesses build inclusive and compliant websites, mobile apps and digital documents. In our conversation, rubra and I talk about how the responsibilities of operators have evolved. We use the partnership between Reb ops and data teams as a model for how ops can and should leverage available resources. And if you stick around, you'll hear Rupert offer one of the more thought provoking comparisons of how different types of operators approach their work. Let's jump right in, though by using an everyday example of Rupert's disciplined approach. And to do that we're going to dissect the partnership between Reb ops teams and data teams, how should we as operators think about and approach that partnership?
Rupert Dallas 1:49
Rev. Ops, I believe is in at least in my experience, the hub in sort of hub and spoke organization, usually everything that has anything to do with generating, you know, revenue dollars, action with a customer usually runs at some point through rev ops right to you, that's through CRM, or any of the other tools to drive excellence and execution. And to drive repeatable results, you need a group within rev ops that does the analytics and the heavy analytics, right. So every rep ops leader should be able to do their own analysis. But you get data scientists that can look for the next level or the nth degree of nuance in a data set. And their job if used correctly. And their results and outcomes, if used correctly, will not only help you build repeatable processes and repeatable outcomes. But they will also point out the places in the areas where you're failing, you're missing, or where that most people don't tend to look in that is the little small things that help a an opportunity go from good to great things like the number of calls you need to make to really understand your customers problems and craft a really good solution. Like that's the level of effort that at least in my experience, the analyst group provides to robots.
Sean Lane 3:10
And you said something important in there, which was if used correctly. And so if you use curl, what does that mean for a Reb ops team to partner correctly? Where the data science team? Yeah, so
Rupert Dallas 3:22
really simple, right? If, in terms of us providing requirements to what we want to see a dataset, or what we want to analyze the dataset, and we want an answer from that dataset, it's different when you say, Hey, here's some data. Tell me what you see, rather than here's some specific data, let's call it like lead date or opportunity data. I want to know what my close rate is, I want to know what my, you know, start to finish whether it takes one call to call three calls, meetings, activities, I need to know those level of details. And I want that analysis back to me. That is the correct way. If I just say, hey, look, here's some data and like, man, your data scientists tell me what you see, that's not going to give me the answers that I want. That's gonna give them an opportunity to play around to do the cool stuff that they like to do, but not provide me with really usable, intentional data.
Sean Lane 4:25
Okay, so if this Reb ops data science partnership is to really work rubric is putting the onus on us, the operators to be thoughtful and intentional about the assets we bring and the deliverables we expect. And from my work with data teams, guess what they want that too. You can't just walk up and say, Hey, you're good with data. What do you think of this? You don't want to box them in entirely, but you need to be clear and concise about the question that you're trying to answer. And what's more, I think the most important role of robots in this partner Tip is to bring the business context behind the ask, so that your question or the deliverable they're asking for, aren't being presented in a vacuum. And it turns out, Robert agreed with me that
Rupert Dallas 5:13
it's 100%. Correct. And I'll give you a perfect example. So we've been embarking on this rediscovery of understanding our entire sales process, not even from like, Hey, I have an opportunity that I've created, even going further back to say, what was the level of effort that I needed to do or to give to have a successful or reasonably successful outcome at the end of this opportunity. And I wanted to really focus on that piece, the effort it takes to get the opportunity, rather than the opportunity itself. And here's the outcome of that request. When I first said to my analyst, team, hey, I really want to know what the effort is to generate a really, really good opportunity, they heard it as we need to look at lead data, we need to look at marketing data, we need to look at the flow, we need to look at all the forms, we need to look at all click rates, we need to look at all of that and tell you how long it takes you to get a lead to come into the door to be an opportunity. And I'm like, no, no, no, no, no. Let me be more specific. I just want to know, once a lead is generated and a person any sales person on my team, they have that lead, what's the level of effort? What's the amount of time that it takes, on average, to generate an opportunity that actually closes in the end, right? That way I can gauge the behavior? They're like, No, no, you understand? You have to look way, way, way, way up, like no, that's not the business case, right? My need is very, very specific, right? Because I want to find that behavior, right at the beginning of setting up a really good opportunity that's repeatable, right? If it's the number of calls, or its number of steps, or the number of emails, whatever that is, I want to find that little bit, I'm not too concerned about what's upfield, I'm just looking for a very specific behavior. And I know that is in the data, that's what I want from you. And when they kind of got that into their head, they're like, Okay, we can do that we can give you that, right. But if I would have just said, Hey, that's what I want, you see how far upstream they went? Like, hey, we want to look at the whole entire process. So
Sean Lane 7:23
if we pull that thread a little bit, right, like you properly defined the business question that we're trying to answer, now, they've gone off and you know, hopefully done, you know, their magic, right, to bring you back some nugget of insight or answer to the question you're trying to solve. I feel like to bring that thing fully to completion. There's this other kind of layer of translation in there too, because chances are, what they bring back might be highly technical, or, you know, maybe too much versus what actually needs to make it back into the hands of in this example, you know, the go to market leaders, right? How do you think about kind of like finishing out the end of that translation and kind of bringing the Partnership on a project to a close?
Rupert Dallas 8:04
Yeah, first thing, I would say, You got to get smart, you know, part of the reason why I can ask very specific questions is I delve into the analytics, right. And so when I get a bunch of results back from the data that, you know, that that was given to my team, you know, I start to really look at what is the actual result? What are the things that they said, hey, look, here, the nuggets, whether it's one or 10. And then to get that back into the leaders, I pick, you know, with them the most probable outcomes, and we test it. That's the key, right? You tested, hey, if they said, look, we've noticed that when a customer comes in, and it's converted to just an incoming potential, and it's a lead, and then that lead is qualified, it takes three meetings, on average, to turn that lead into an opportunity, that gives you a better than 50% chance of closing, right? So that outcome is easy to test, you know what I do? I go to my head of sales, and like, hey, I want to see that before they convert these. I want to see these three people or these two people have three meetings, right? And then I can say to the rest of team just go on as business and I can do that for a month. And if the outcome is more of their opportunities close or close at a higher rate. I know that's the key right? Then I can say, look, here's the data that supports this. Here's the test that we did that prove this outcome. Analysts team. Do you agree? Yes, we agree. Let's go. That's what we need to do. That's what we need to focus on.
Sean Lane 9:36
What Rupert's describing here is basic. formulate a hypothesis using data to test your hypothesis, validate or disprove it. It's the execution in the details of his test that I find impressive. He's disciplined to only test his hypothesis with a select group. He doesn't just go straight into changing everything based on a single file. Finding and look, that discipline, it comes from practice. If you're listening to this, and you're not a data scientist, which most traditional Reb ops folks are not, this whole process might feel a bit intimidating. But Rupert says, We got to get smart. So let's break that down. What's the common language we should develop to even be able to approach a data science team and start this partnership off in the right way,
Rupert Dallas 10:27
I started with just trying to understand the tools that they use, we use, of course, we use Power BI, we use MetaBase, we have a tool called stitch that takes disparate data sets, and they you can be able to do, you know, stitch them together, I really, really want to work on really understanding the difference between like a report and a model, right. And for them, I start talking to Geek wars, right for them. If that is a huge difference, it's a huge difference. But when you understand, hey, I'm building a model to test something. And I'm giving you a report that has an outcome that shows the result, those two things are different. And when I started to understand that, and like jumping into their tools, then they had enough trust and confidence in me that that I could actually give them very, very clear. And I say clear requests and requirements for them to generate the outcomes that I'm looking for. That was the way that I got smart. I
Sean Lane 11:24
really liked that distinction. And like, I guess at what point do you think, you know, you were ready to be able to have those conversations, right? If I'm someone listening to this, and I want to get smart, like, does that mean I need to go take a bunch of data science courses, like what is good enough to be able to build the type of successful partnership that you've built, without, you know, coming to the table with nothing?
Rupert Dallas 11:48
I'll take it all the way back to the beginning of our conversation. If you take a generalized statement to anyone in your analysis group and say, hey, I want to know, you know, what the repeatable behaviors are that I can have my salespeople provide or do so that I can generate the best outcome. Just take that answer that they're gonna give to you. And it's gonna be big, it's gonna be broad, right? Hey, I'm gonna look at this, I'm gonna look at this, I'm looking at this, look at these things. And I'm like, Hey, all right, let's just take them one at a time. Let's just take them one at a time. And I chose to take that piece the closest to the opportunity to opportunity start, that's the piece that I decided to focus on it and just doing that, you're able to take that big world, you know, universal question and whittle it all the way down to something that you can take off in bite sized chunks, whether or not you're an expert or not. And that's what's important, right? Most people in rev ops are going to be able to see a big problem and break it down into smaller problem sets. And even if they don't know how they can just take the, you know, put it all out there. And now that you've identified what you're going to do, I only want to pick this one little piece and focus on that first. That's the best way and the best advice I can give to someone who's not an expert, especially, we're most of us are not data scientists, but an expert way of saying I can get to very specific answers, by really starting with the bigger picture and whittling all the way down to that one thing. And I
Sean Lane 13:17
think like the flip side is the value that you are bringing to the table that you probably don't even recognize, right, like what you just described, being able to whittle that down to a question like, that's a skill set, being able to bring the business context that we talked about before that the data team or the data science team might not have, like, that's a skill set. And we're so quick, I think to be self critical about what we can't contribute or don't know, the right, you know, model name for. But in reality, like, there's so much that we bring to the table in that interaction as well.
Rupert Dallas 13:47
Yeah, I mean, I took statistics in college, and I couldn't remember what a two tailed t test actually does, right. And I couldn't remember what statistical methodology was because I mean, I haven't been using that in 20 years. However, I do know what like a unique value is and I can understand like, what probabilities are and I know what a bell curve is, right? And I know when they say, Hey, look, your highest probability to reach your outcome is x, like I could look where that is on a graph. And most people, you're laughing, but most people can do that, right? Yeah, the trick here is being able to phrase it in a way that you can get to that leads to that outcome, right, where you can point to something on a piece of paper, I'll be
Sean Lane 14:26
completely honest with you all. And don't tell anyone at my company because they think of me as the numbers guy. But I was a communications major in college. If I can properly use the word quartile in a sentence, I'm having a good day. But what Rupert is talking about, at least on the robot side of this partnership isn't advanced mathematics. It's pattern matching and problem solving. Rupert saw a problem and instead of letting the scope of his answer get wildly out of control, he instead narrowed his focus down to the most specific big point that he could address that problem and that problem alone. Again, the word discipline comes to mind. And from my conversation with Rupert, it became clear to me that he is thoughtfully developed his own disciplined approach to ops as a whole. As he's watched his role and his responsibilities evolve over time. I
Rupert Dallas 15:22
will say that for me, getting into rev ops, I started on the sales ops piece of this right where it was just a, as an operator, you just operated or you admin or you manage your CRM, and in this case, mine has been Salesforce for the past 1520 years. And then you do your regular stack, right, and you manage that and manage a little bit of the analysis, but you partner with everyone else. For me, that changed when they started to add on responsibility. When I took on more responsibility beyond just Salesforce beyond just our tool stack, it became a real passion of mine, when we started to integrate marketing ops when we started to integrate things like having a representative from product and product operations and product marketing show up to the table to really put inputs on what the desired outcomes are, when they come to the table. And then you start to really get synergistic about creating better outcomes. And that was a light switch. And man, I jumped in, you know, running to the beach, taking off all my clothes like this. And ever since, like that realization, like I've been so passionate about how do we create a really, really high functioning Reb ops team by making sure we have representatives from all the parts of the organization that contribute to generating revenue. And the thing that sometimes
Sean Lane 16:51
I get nervous about right, when you're adding in all those different functions that you're describing, and saying, Okay, this is going to be this centralized resource across all these different parts of the customer journey, marketing, sales, sometimes customer, right, some of that makes me nervous sometimes is that the breadth of stuff is getting too big, right. And so because there's so much stuff, what is now starting to happen is everyone's kind of definitions and approaches to DevOps can be slightly different depending on the company you're in and the structure of your team. You've also said, though, that within that spectrum, you're also seeing just the approach that operators take to Reb ops itself, you've seen a little bit of a schism there too.
Rupert Dallas 17:33
I have in that is, that is a, I think, a result of the difference in and I don't want to use the word age, but with time and space or time in service, right? Okay, there's a huge difference from the people that I would call my longtime peers, the way we think about rev ops, compared to the folks that are coming up. Now, I'll just go out on a limb and say this, the folks that are coming in now they're much faster, they're much more into technology, using technology and automation to solve everyday problems. Every year problems, where we are, the older I get, I am more of taking a step back in really looking at what resources do I have at my disposal to really attack a problem, even if it's an everyday problem, or an every year problem. And that difference, that divergence is a huge, as you said, schism, in sort of the old guard and the new guard, right? Using technology using automation using ability and will and information pure straight tip of the finger information. Versus I have a team or I mean, I have a team, but I have resources in the company, I know that I can go to Marketing to really investigate an issue or I can go right to, you know, to product and like, Hey, I'm seeing on the sales side, that customers don't exactly like this part or this portion of our software, you know, can we change? Have you done an analysis to adjust that, like, that's the way that I think versus Hey, what's the data tells me right away, that it's on my fingertips, or I can go and query any system or you know what, you know, I can build an app and do it myself. Like, that's a huge difference in just approach. And I think that's where you will see the gap. Even if you put the same people on the same team. That's that gap, which is all my team, that gap is still very present. This split in
Sean Lane 19:33
approaches is worth exploring. On one hand, you have the group Rupert considers himself in along with his contemporaries, and he's saying that that group is more willing to take a step back when faced with a problem and thoughtfully applied the resources available to systematically attacking that particular problem. And then on the other hand, you have this group of new operators, which he describes as running towards the problem and quickly if not, hey, slowly, trying to get information at their fingertips as quickly as possible to solve it, usually on their own. Think about that for a second. Which group do you fall into? Which group do your teammates fall into? It's pretty thought provoking. Right? So how does this difference in approaches reveal itself in the work that we do?
Rupert Dallas 20:23
Here's ruber. Here's an example that just blew, I mean, this happened literally this week. So we're trying to figure out, you know, what, paid advertisements that we are paying for that are producing the best results, right. And, of course, our the person that runs paid advertising for our team and marketing, he jumped right into like Google Analytics, he looks at our page views. And he's like, Man, I'm just like, we can do this. And we can do that we can start making changes. And I'm just like, well, is the language on those ads resonating with people? And he literally just looks at me, like, he looks at me. And he was like, I don't know, I didn't write the copy, or I he's like, I don't know. And I'm like, Well, I mean, at least let's start there. Like, great. Let's go jump in. But let's at least answer that question. Right, the simple question of does this resonate? You know, is this attractive enough for people to actually, you know, dig deeper, right? More clicks means more views, more views means a higher chance of them actually coming to our system and becoming a customer? Well, is the beginning of that is the actual stuff that we're putting out, does that resonate to drive clicks, and he was like, I'll get back to you. But that's, again, on the same team, same goal, approach completely different, right?
Sean Lane 21:43
And like, I had a boss, and one of her favorite sayings was slow is smooth, smooth is fast. And it's basically the approach that you're describing. And so how do you help people on your team, or folks who might fall into let's call it like, the newer camp of the fast tech automate, go, go go? How do you coach them to recognize the value of that, hey, let's pause for a second because guaranteed they're getting pressured by somebody else, right? They're getting pressured by a sales leader or a marketing leader or rep, a manager to say I need this, and I need it yesterday. So how do you coach people through those situations?
Rupert Dallas 22:25
First, I love the excitement, and the energy and the ability to maintain such a high pace with like, high productive contribution of the young people on my team, I man, trust me if I had their energy. And if I could work as fast and as hard as they do in the short amount of time that they do, man, my production will be so high. And I kind of I encouraged that in the beginning, right? I'm like, Hey, here's our problem, problem statement, go out, and I let them go, I just I let them run. But I don't let them move beyond a certain point before coming back. I'm like, Alright, let's deconstruct this, right. So that I'm both getting their effort, their energy, their pace, but I'm managing the results and managing the outcome from that work. And that's how I teach them, right. That's how I take them to get the moment have I did all this work. But did I really, actually get to the thing that you asked me to get to, for instance, I'm gonna do all this work, I'm gonna go look at our AdWords, I'm gonna go do this, I'm gonna do that. But it didn't really think about what the question is in is, is that does the thing that we put out there generate enough interest for someone to actually click? Let's just start at the beginning, rather than just starting with the data. Right? And just having that conversation was like a lightbulb moment. And it's that teachable moment that next time that this comes up, they'll be like, Okay, I'm gonna go work. But let me ask, is this the exact question that I'm going to be providing the outcome to, and those teachable moments just happen on a natural basis. But more importantly, like, you got to let them run, you got to let them go to go do the work first, before you can provide that time where you can have a teachable moment.
Sean Lane 24:17
And I think those teachable moments are applicable, both in a project specific environment, but also in kind of like an ongoing running the business context, right? Like, because if you are just constantly looking for that next report, or that next thing to answer the questions that you are going to have to answer every day, week, quarter year, all you're doing is creating a situation for yourself, that's going to be more painful, right? And then you basically end up with you know, we're going to track 27 KPIs, and no one really knows what's actually going on with the business because all we've done is reacts to the requests as they've come in. And so to me, that's the other part of this which is like you're helping them To see around corners for why this new thing might break, or the follow up question that someone's going to ask to that single report that they might have built that they thought had the critical answer. Am I thinking about that the right way? Yeah,
Rupert Dallas 25:13
you absolutely are in, you know, this phenomenon, I will call it a phenomenon where people tend to miss, like, the critical step. And a chain really happens when there is an event or a campaign. And it's after a campaign and it's after campaign and there is no area, there's no space for really thought out. really intimate, backwards looking perspective. And what I mean is by, before moving forward, let's have a post mortem. Where did we fail? Where did we knock it out of the park? What are the lessons learned? More importantly, what am I taking, and I'm applying to the next one, right. And that's also a teachable moment. But the only way to get to those is like is to have that stop, right not to, hey, we finished this campaign on Monday or Sunday, and we're starting the next one on Monday, and we're going to run and we're going to go after it and everybody else you can do analysis and figuring out what's working, then you tell me to make the pivot or the adjustment while I'm already in it. Like I've seen companies run that way. I've seen teams run that way. You know, a lot of Sprint's are run that way, hey, we do this two weeks sprint, at the end of that sprint, we have a result, and it's all to the next two weeks sprint, without taking that time that gap in the in between to like to really, really do the breakdown, what was good, what was bad, what he learned, were we taken forward, what are we just not doing ever again, and take that lesson into the next. And you can actually do that in a really functionally timely fashion without taking too much time. So that's away from, you know, the job of being an operator, especially as a leader and an operator.
Sean Lane 26:54
Anybody else sitting there thinking about how incredible it must be to have Rupert as your manager. And not just for the experience of being an individual contributor on his team in that type of environment. But the lessons that his team members must learn that they will inevitably take with them, whether they realize it or not, when they go on to become leaders themselves. I really admire him for it. I also acknowledge that his discipline may feel both idealistic and unrealistic to some of you sitting there with this endless list of projects on your plate. So that begs the question, how does Rupert take the theory of what he's describing, and ensure that he has the discipline to consistently put it into practice? It's hard.
Rupert Dallas 27:41
I mean, the pure, simple answer, it's hard, very, very hard. But there's also a saying, like, with age comes experience. And I don't even think that's correct. I just think that with time comes experience, and I've had enough time to get myself into enough trouble. Or like, no, I really did get hurt enough, I don't want to do those things again. And like, and I would rather impart or download that pain into someone so that they can avoid that and avoid at least my own mistakes. And so that they are better, you know, at the beginning, or we are better together at the beginning, rather than, you know, let them run, let them make their mistakes, and then be like, Hey, pick them up, brush them off. Here's how you fell down. And I'm like constantly doing that, right. And that's why I take the time. And when I say it's hard, it's difficult because they're moving fast. And my inclination is also to move fast, right? Let's try and keep up rather than let's take a couple deep breaths, let's have a glass of water. Let's plan some time on my calendar. And let's say it's two hours every, you know, two weeks or every week, and like I'm calling it all stop, and we're just going to talk about stuff. And we're just going to catch up with each other, we're just, we're gonna stop. And again, the result about that is it's better in the end like you get a better result. In the end, especially if the long term project like some of these campaigns that we develop, they can go on for months and months and month. But if you don't take the time between the last one and the next one to like, really set yourself up for success. And like really do a post mortem, you're going to take that baggage into an especially if it's bad baggage into your next campaign or into your next project into your next event and the eventualities you will not be as high of a performer and that's why I learned like you've got to stop and and again, it's hard but don't take my advice. Take the hard knocks. And then you will learn for yourself that you need something like this
Sean Lane 29:53
before we go at the end of each show, we're going to ask each guest the same lightning round of questions. Ready? Here we go. Best book you've read in the last six months.
Rupert Dallas 30:04
Oh, right here. I have it right here on my desk. Getting to Yes. Love it. Getting to Yes, yeah. It's a fantastic book about not just negotiating in business, but negotiating in life life terms. It's also about not figuring out what consolation prizes you have to give, or to get to feel that you've gotten something equal out of the deal, right? Most deals are going to favor one person or the other, even though it feels like it is a 5050 split. And that the understanding of that mental philosophy is a huge unlock when it comes to negotiating.
Sean Lane 30:49
That's super interesting. All right, putting on the list. favorite part about working in OPS, never
Rupert Dallas 30:54
having to see the same problem every day. That's I mean, talk about the person who has ADHD, talk about your dream job. You don't see the same problems on a day to day basis. And that change in scenery and an outcome is fantastic. If you can't focus on something for more than 24 hours. All
Sean Lane 31:18
right, Flipside least favorite part about working in OPS, the fact
Rupert Dallas 31:22
that I see something different
Sean Lane 31:26
you know, serve that up on a silver platter for
Rupert Dallas 31:29
you know, my least favorite part about working Ops is having to deal with the uncertainty in the beginning of any evolution, right? I've planned. I've done everything I've can I've set up Salesforce, I'm ready to collect data. And it's the day before at that moment, before something launches their their product, launch or campaign. You go through a mental checklist, and it keeps you awake, like did I absolutely do everything that I possibly could to make this a success. And in that piece, keeps me awake at night. And that first day, I am on edge because my expectation is that I've done everything, but then nobody survives, like the first, you know, encounter with the enemy. And that's what I don't like I fear that and I don't like it. Alright,
Sean Lane 32:22
next one, someone who influenced that you get into the job you have today?
Rupert Dallas 32:26
Wow, there's been a lot of influences. I will say that the first person that told me to go out and fix my sales problem was an old sales manager. His name was Jim pode. And if Jim didn't tell me to go and stop, you know, complaining and go fix your contracting problem with the sales ops people, I would have never been exposed to this. I would have stayed on the sales side. And I would have, you know, gotten success that way. But he told me go fix it. And I have not left ever since. Thank you, Jimbo.
Sean Lane 33:02
That's an awesome story. That's awesome. All right. Last one, one piece of advice for people who want to have your job someday.
Rupert Dallas 33:10
You know, listen to this interview, I gave a couple pieces of advice right? About slowing down taking some time in between events, projects, moments, have teachable moments. And if you're on the receiving end, really take those moments to heart I have had, again plenty of opportunity to fail and to fall on my face and to be picked up and to make my own mistakes. But if someone cares enough about you in your position is put enough interest in you to keep you from failing. take that to heart and internalize it execute operate on it and it will extremely accelerate your career.
Sean Lane 33:55
Thank you so much to Rupert for joining us on this week's episode of operations. If you just listen to this episode, it will come as no surprise to you that Rupert was recently named to the modern sales 2022 list of the top 100 revenue operations leaders. Congratulations Rupert. If you liked what you heard, and you learned something from Rupert today, make sure you're subscribed to our show. A new episode comes out in your feed every other Friday. Also, leave us a review on Apple podcasts wherever you get your reviews, six star reviews only it really helps other people to find the show. All right. That's going to do it for me. Thanks so much for listening. We'll see you next time.
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