Sean Lane 0:01
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Hey everyone, welcome to operations, the show where we look under the hood of companies in hypergrowth. My name is Sean lane, shifts in business models are really interesting to look at if you spend most of your career in a particular model, it might be difficult to translate some of the things that you believe to be foundational into a completely different model. A great example of this is operators who are used to the typical SaaS subscription bookings model, but all of a sudden find themselves working in a consumption or usage based business in the typical subscription bookings model, the customer signs a contract, they commit to a particular period of time, and they pay you for that period of time. Simple enough, right in a consumption basis, the customer pays you, not necessarily for a predetermined flat amount, but rather based on how much they actually use your product. Now look, I'm not saying that consumption based businesses are new. We all pay our electric bills this way, right? But consumption based businesses, particularly consumption based software, businesses, are definitely on the rise, and with AI powered tools becoming more and more prevalent, the often default seat based model in SaaS, companies might see some challenges in our near future. So I wanted to talk with someone who understands the nuances and complexities that are required to run operations within a consumption based business. I found that person in Lauren Davis. Lauren is the director of revenue operations at checker, where she has spent the last six years rising through the ranks of various ops roles. Checker, if you're not familiar, specializes in background checks and employment screening, and they've raised more than $600 million in funding. And you guessed it, their business model is based off of the number of those checks that their customers use. In our conversation, Lauren and I talk about all of the systems plumbing that required a level of complexity in a consumption based business. We talk about whether her six years of institutional knowledge are an asset or a burden to the work that she does, and she reveals the single biggest compensation mistake that she made in her work in comp design at the company. To start though, let's learn a little bit more about checkers business model and what makes it complex? Here's Lauren,
Lauren Davis 3:05
so we are a background check provider, and we have a consumption based model, which is very, very common in the background check world. And what that means is, unlike traditional SaaS, where you sign a contract and you are kind of locked into that contract for a year, you do still sign a contract with checker, but it is based on usage. So we don't actually make money until you start spending, unless you have signed a commit, which I'll talk about in a second. So if you think you're gonna run, you know, let's call it 100 background checks in a year, right? We think that you are a certain size customer, if something like covid happens, and maybe that directly impacts your business, and suddenly your business isn't doing as well, and then maybe you're not actually running 100 checks that year. The opposite can happen as well, right? Something can take off. Maybe you get new funding, and you're growing your company, and all of a sudden you're doing 1000 background checks. So we kind of grow and with the company based on how they're using the product.
Sean Lane 4:07
Got it super helpful. And I want to get into all the nuances of that, but even just in that very short description, you were talking about the number of checks and usage and a committed amount, and I would imagine there's just this whole Glossary of these, you know, foundational terms and definitions that you just have to get right and get everybody on the same page on in order to run a business like this. Am I onto something there? Is that right? Yes,
Lauren Davis 4:33
yes. Data definitions is a big part of my job, a big part of Rev ops, product finance, can cross the whole organization. So even if you think of something like a customer, which in a lot of companies, customers relatively straightforward, that is something that we have to have many conversations about, and align on a definition. We have aligned on a definition. But I would say even like there are differing thoughts and opinions. On that within the company. So again, you can sign a contract, and then what happens if something happens and you never end up spending Are you a customer? Are you only a customer and you spend money with us? If you do not, all of our products are usage based. We have some products that are subscription based, right or platform based, and so if you spend that, but you don't actually use the platform like is that a customer? And so there's all these different like facets of it that you have to really get very tight on, what is the business definition, and then also what is the technical definition of that, and how would we report on that consistently across the business?
Sean Lane 5:37
And I would imagine even if you do the really hard work of getting everybody on the same page documenting those definitions. You kind of hinted at it there that, like, there's still going to be some holdouts maybe, right? Or there's still going to be folks that are going to forget old definition. Is actually the old definition. Now there's a new version of this definition that, like, you have to forget about the old one. Can you just take us inside that process a little bit both of how you arrived at the definitions you have, and then also, how do you kind of maintain the freshness around the definitions that everyone needs to adhere to and run the business off of? Right? Because if somebody's using last year's definition now, they're going to come to the table with a totally different set of data and reporting than the rest of the company.
Lauren Davis 6:18
Yes, so the key there is to make sure that we're all using the same data models and the same data infrastructure, and so that no matter how you're reporting on it, you are reporting on the same thing, right? They are definitions that we talk about constantly. So I am in these conversations right now as we're heading into planning daily. So even if we don't change the definition, I would say we definitely reset and approach like, does this definition still make sense for where we are as a company, at least annually, as we do annual planning, which I also think helps with some of that differing of opinion, right? So if some folks come in and maybe they're like, oh, I don't agree with this, it's like, okay, let's, let's hold on, right? Like we did all of our modeling, we set all of our targets off of this initial definition. Let's have that conversation as we go into planning. And then oftentimes too, it's like in these conversations, which are simultaneously some of my favorite conversations to have with folks around, because it's just intellectually stimulating for me, at least around, why do you think that way? Why do you think that way? And also kind of Groundhog Day, having been at the company for six years, right, where people come in? I was just in a conversation the other day where we were talking about customer segmentation, and I was like, Oh, now we're talking about a definition that we actually had, you know, a couple years ago. Like, was that the right definition? Right? So I think that dichotomy is really, really hysterical, at least from my perspective, but I think making sure you're constantly approaching those definitions to make sure like they're right for the business that you are today is really important. And then, to my earlier point, of making sure that we are consistent with who we loop in, how we communicate out, and then updating, most importantly, the data infrastructure so that even if somebody doesn't know, let's say, you know, we changed our definition of a customer just since we were talking about that earlier, even if somebody didn't know that we did that, if our data models are updated appropriately, and they're pulling a report to see like customer acquisition, over time, it will just have updated. And so we do a lot of work as well to make sure we're updating historical data and also not losing that historical data so we can always look at like, okay, based on how we looked at our business in 2021 How does that look over time, versus how we look at our business today? All
Sean Lane 8:33
of this definition work falls into the category of no one except ops truly appreciates and understands the depth and impact of just about everyone else will be the recipient of this work. Yeah, some will question it. Some will get engaged in the nuances. But Lauren says she talks about these definitions daily, and she likes it. To me, the institutional knowledge that Lauren has and the historical ripple effects that she understands cannot be undervalued. But I've also found that institutional knowledge can be a bit of a double edged sword and ops. Does she remember too much? Does she have too much historical context? Does she remember too much about the politics of the time when a particular decision was made? So I asked her if she thought that her institutional knowledge was an asset or a burden?
Lauren Davis 9:23
It's a great question. I think it depends, right? And transparently, it's something that I've also had to acknowledge and recognize in myself, because there have been conversations where sometimes I feel like we are going backwards, so to speak, right? I'm like, Okay, well, we did that that way three years ago. Why did we change? And it's important to recognize that, like in myself, because just because it might be going backwards doesn't mean it's wrong, right? Like, maybe we got it right the first time and we changed things for one reason or another, but that either didn't pan out. Or we found new struggles, and we should go back to the old definition, right? So like segmentation is one we talk about all the time for a number of different reasons. And we've gone from looking at like the type of company, like characteristics, from a graphic information to looking at like spend patterns, to looking at like volume patterns. And that is one that I personally find is very, very complex. I personally find it challenging and also a little like mind numbing at times. But that is one of those things where it's like, okay, we made this change. Here are the benefits, here's the new problems it presented. And I think that's really important to like parse out of like, okay, why did we make this change? And I do think that context is important, because sometimes that is missed for one reason or another. And then did we actually see that benefit? And most of the time we have, but then it's also presented like other challenges for another reason, and then it's really just weighing is that new challenge? Is there another way to deal with that, or is there a better way to deal with that? Or do we want to go back and try and solve the original problem? And I think that's the helpful context there, because sometimes everyone's always trying to find a silver bullet, right? And so you think, especially like, if you come in and you're like, Oh, I think we should do X, like, this will solve all of our problems. And I think oftentimes people forget that it will oftentimes present other problems that may not be as big as the other ones or unsolvable in some other way, but it's rare that you find a silver bullet of like, okay, now suddenly we don't have any challenges in this area.
Sean Lane 11:45
Everything Lauren just said in the past two or three minutes, that's what it's like inside the head of an operator. The trade offs, the dichotomies, balancing effort and impact with conflicting opinions. That's the job, if you need to articulate to one of your stakeholders what your job is like, send them that clip. All right, let's dig into this data architecture that Lauren has mentioned, as she alluded to, instrumenting and measuring a consumption based business is a bit more complex than your typical annual subscription SaaS bookings business. So if someone were to be looking for the key metrics, the basic building blocks that you need for a usage based business, what would those be? I
Lauren Davis 12:28
actually think a great example of this is we've been in a lot of conversations recently around, how do we define upsell? And I think this actually hits exactly at what you're talking about. So upsell in a lot of companies is, like, relatively straightforward, right? I literally, in one meeting, pulled up, like, the Oxford definition of upsell to like, help us orient. And I do think sometimes that is also very helpful. Of like, a lot of us do come from traditional SaaS backgrounds. So it's like, let's refer back to what is it like in a SaaS world, and is this a lot more straightforward and easy. And can we take components of that, but an upsell specifically that maybe is more straightforward in some traditional SaaS worlds, we've taken the approach of like, what are all the elements of potential upsell, and how do we track all of those specifically? Right? So it is, are we increasing the price of an existing product? Are we adding new products? Is there volume increasing, right? So those are, like the components. It's not just, you know, revenue equals volume times price, right, times like number of products. And so it's tracking those three components, and then it's also tracking potential, like down sell, right? So the variable, the one that makes this really complex is volume, because volume is and is not simultaneously something that you control in a usage based world, right? So there are things that you can do to try and increase volume, whether that be like in our world, increasing the candidate pool. So like things that we can directly control, right? So if you are using checker to run background checks for a portion of your business, can we get you to also use checker to run background checks on another portion of your business? Right? We could say, All right, if we reduce your price for this, will you run more of this type of check, right? So one thing I do want to caveat is, like, oftentimes people will say, like, oh, just check. Or do anything more than just background checks. I'm like, we don't realize is, we have like, hundreds and hundreds of products, and background checks are incredibly complex, and it's not just, like, one size fits all right. So that is actually part of what I think is really fun, is like also educating people on the different types of checks. But at the same time, if your company is doing very well and you're growing and you're hiring more people, you could be spending more with checker from us, not really necessarily doing anything from a sales perspective. On the same side, you could also be spending less if your company's not doing well, and that is part that makes something like an upsell or even just sizing the initial deal incredibly complex. And we always have this saying internally. We always say, like, control. What you can control? Like, what can we control in this situation? What are the levers that we can impact here. So that's kind of how we think about something that in other worlds might be relatively straightforward, what is that upsell? And in our world, it is breaking that down into the individual components. And we want to be able to measure all of those components so that we can figure out, like, what is really going on here, right? So like, if you have a customer that is spending, you know, $100,000 and all of a sudden they start spending $50,000 first of all, it's not all of a sudden, it happens over time. And second of all, you have to dissect why. And you really want to understand why, and sometimes you can do that via data. Sometimes you have to talk to the customer, and so there's a number of different components, but being able to measure that granular level is very important.
Sean Lane 16:07
And I want to get to how you use all of those things in running the business. But I also know from experience that, like, you can't just take all of that granularity for granted, right? Like that just doesn't happen. You don't just have hundreds of skews and different prices and different usage metrics by accident. And so can you talk a little bit about how you as a team have set up the infrastructure that makes all of the operating rhythms of the business possible? Because everything you just described, while it sounds straightforward, is very complicated to put in place. So how have you all gone about doing that so that you can be confident in all of the granularity that you're talking about?
Lauren Davis 16:54
Yeah, and I think this is really important to call out, because I think oftentimes when people think about rev ops, revenue operations, oftentimes we sit in revenue we support our revenue teams, right? Marketing, sales, customer success. And I think what sometimes people forget is all the other teams that rev Ops is working with as well. And so exactly what you're talking about is incredible alignment, constant coordination and constant conversation with teams like product and finance and billing and accounting, right? And like making sure that we have this really, really tight machine so that when product is rolling out a new product, we understand how that is billed, how we will quote that from a sales perspective, how we need to build that into CPQ so that all the systems can talk to each other and that we can report on it, and it is across a number of different systems. It's the product, it's Salesforce, it's our billing infrastructure, and making sure that everyone is in alignment is just like constant conversation like I often say, revops is like, more so than like, any of the technical skills and like hard skills, right is just a lot of, like, making sure the right people are in the room to have visibility into that and like, over communicating. The thing that
Sean Lane 18:14
struck me and all of that coordination that Lauren just explained, is that you can't skip over this type of preparation in this business model, in a typical bookings business, you might be able to launch a new feature, run an experiment, or just be scrappy without all of the plumbing actually being hooked up properly between the product and billing and all of your other systems. You can't do that in a usage based business. Everything needs to work now if you have all that plumbing working, how do you then actually run your business? That's right after this. If you're spending too much time building and rebuilding sales reports and dashboards, it's time to look into Tiger eye. Tiger eye helps rev ops teams scale without adding headcount. Powerfully simple, go to market. Data is available to the whole team. Lightning fast. Dig into what's working, where deals are getting stuck, compare current quarter to historicals and track your growth. Tigray helps rev ops teams predict and guide growth. Schedule a demo [email protected] Okay. Back to Lauren before the break. Lauren broke down for us all the definitions, collaboration and instrumentation that you need to have in place for a usage based business to work. But if all of that legwork is different than in a typical booking subscription business, then how does someone like Lauren actually run the operating rhythms, pipeline creation, pipeline management, forecasting in a business like checker, yeah.
Lauren Davis 19:46
So let's start on the new biz side, because I think that's like, just a little bit more straightforward. The way I think about it is it just like extends this process, right? So oftentimes when we talk about pipeline, we think about pipe. Line up until close one, right? The life cycle of the opportunity within Salesforce in a consumption world, that's not where pipeline ends. And like you know, spending and revenue begins, it's actually a step further until when they actually start in our business, running checks, right? And actually start spending. So the way I think about is like, your pipeline management is anyone who is not active, and then even when someone's active, that's like a different group. But there's almost like these, like three stages. There's open pipeline where you haven't actually gotten them to sign a contract yet. That one's relatively straightforward in like, SAS world, right? But to your point, we do make a lot of assumptions in terms of, like, volume of checks that we expect them to run. So some businesses have a lot of history here around, yes, this is how many people we hire last year, when we ran background checks, we ran 100 right? So we're probably going to do 100 again, or we're thinking of scaling this year. So last year we ran 100 but we're thinking of doubling. So we're gonna run 200 if they haven't run checks before. It's talking about like turnover within their business. How many people they plan on hiring? Things like that. And then there's also a lot of education around what are the types of checks you need in your business, right? So going back to the comment I made earlier, background checks are incredibly complex, people hear things like, Oh, if it's the national criminal database, it must be like, encompass all of the criminal court records, right? That's not the case, right? So you need different levels, and so being able to educate the customers as well around in your business like these are the types of checks you might need. So those are the components of like within actual pipeline, or what normal like SAS world considers pipeline. Then you get them to sign the contract. They haven't actually started spending yet, right? So then we enter kind of the second phase of pipeline, which is really around, how do we get the customer live, how do we get them set up successfully? How do we get them integrated. How do we get them to start spending? That is like we often refer to that time of between like bookings to revenue conversion. So it's just another conversion metric we're thinking about in our funnel. And then the third one is, once they've actually started spending, are they ramping at the rates that we expect them to? And we have a ton of data on based on size of company, segment who sold it, types of products they're using, like industry, all those fun things around how we expect that to ramp over time and tracking to that. So if you see a customer maybe spending a lot less, really, like being all over that in terms of, why are they not spending at that level, and making sure that the sales rep is attached to that deal throughout the entire time, because they are the ones who ultimately are, you know, driving these new customers and revenue, and have the historical context and background around, like, what we do expect those spend patterns to be and why?
Sean Lane 22:58
And, you know, people talk a lot about forecasting as this, you know, blend of art and science. And I would have to imagine in your world, it is much more science than the typical SaaS business in terms of the mix there, not necessarily that you're, you know, the answer. You have a bunch of assumptions to make, but probably less input feeling subjectivity from a rep and their manager than the data driven version of it. Am I? Am I right there? Or is it different?
Lauren Davis 23:30
I think it depends on the segment. Okay? Because when you're up market, it is still, and this is very typical in SaaS too, like I've been at large enterprise companies where it is all you know. Do you think that this deal will close? Right? Like individual deal by deal, the enterprise world is still very much like that. You do have large enterprise companies where their lead time to go live is much longer. They're evaluating for much longer, like that. That is still very typical. And then you also have, like, more down market, where it is a lot of data, right? So even in our like, small, small end, we've experimented with just, like, really reporting on like number of customers signed, right? And then, like, just taking all the data to basically say, how quickly do we expect them to ramp in terms of revenue and spend? And so it really just depends based on the segment. The thing that is difficult, even in that upper market or lower market, again, going back to that volume comment from earlier, is like, there's also a lot of like, what do we think the market's going to do? Right? So in, you know, 2020 like, no one could really kind of predict what covid was going to do. And that was a wild time for a number of reasons. 2021 with the market rebounding like there is. You can have the sales rep predicting things. You can have a lot of historical data thinking about, what do we historically see from customers that look like x? We expect their spend to look like y. But then, when you introduce like this. Market economy, there's also that's the art part of the forecasting, in my opinion, because you're having to look at so many different dimensions to really kind of understand where we think we will land with a certain customer. From a revenue perspective, from what
Sean Lane 25:17
I'm hearing, if you run a business like checker, you have to be able to build intelligent assumptions into every phase of your model, open pipeline, volume of checks and human implementation behaviors, not to mention the market conditions she mentioned that are probably entirely out of your control. Another thing that stuck out to me, though was Lauren's point about keeping the reps involved until the company actually sees revenue. This isn't your typical send a net 60 invoice that shipped off to an accounting team the company that is your customer actually has to use your product for you to make money. And Lauren mentioned the magic word at the end of her answer, compensation. So how does she design compensation plans in order to incentivize these behaviors around activation and usage
Lauren Davis 26:05
compensation is a fun one. It is ultimately like what you want in a comp plan is, what do you want to incentivize the sales rep or person to do or bring in for the company? And ultimately, like that is revenue. One of the things that is difficult is that, unlike in a SaaS world, where when it's end of quarter and you're trying to hit your number and you're trying to get those contracts in, it doesn't work that way in a consumption business, right? You can still get your contracts in, and we still do pay attention to bookings for a number of reasons, but that doesn't necessarily mean more revenue. So one of the fascinating conversations I think we have is okay, even if we do everything we can to get that customer to sign this month by end of quarter. You know, it's the end of June, so do we try and get them to close by, you know, end of q2 if their plan to go live still hasn't changed, right? So it's not actually pulling any of that revenue forward. So that is the hard part. When it comes to compensation, you want to balance those two elements of driving revenue, which is ultimately like what we want as a company, as a business, what we want sales reps to bring in, but also giving them control around hitting their target and feeling like they can really, like, if they are behind, what can I do to improve my number? Whereas, if it's purely and entirely revenue, that becomes a little bit more difficult. Although I do always say, like, the one thing you can do is like, get those customers to go live. So I think this also goes back to the earlier conversation around what do you consider pipeline? It's that second bucket of pipeline too, right? So when you're approaching the end of the quarter and you're behind, can you get any of those customers that are in that non live bucket to go live faster than they want to do? So from a comp perspective, like those are the two elements that we're constantly balancing to try and incentivize them,
Sean Lane 28:03
and I would imagine there's also an element of trying to translate all that complexity into something that is simple and digestible for the recipients of the plan itself, right? Like, it's never fun when people don't understand how or why they're getting paid, or how to impact the plan that they have in order to make more money, right? Like the whole point is that people should feel as though they are in control of the outcomes that are going to show up in their bank account. But I would have to imagine that's hard in this context. And so how do you help folks to kind of translate the work that they're doing, the types of deals they're closing and the usage of their customers into those types of outcomes.
Lauren Davis 28:51
Yeah, it's hard. It's hard, especially since a lot of folks are coming from a SaaS world where that is so if we have reps coming from a consumption world, it's much easier because they're kind of used to it. A lot of folks come from the SaaS world, so that is a hard hurdle to get over, right? But ultimately, there are still levers that you can pull. So closing more customers, right? Like, that's the kind of like, easiest, straightforward one, right? Getting those customers to go live, assigning them to commitments, if we can, getting them to pay those commitments up front, getting them to revenue and spend faster, right? So working with them around you know, you say your plan is to slowly ramp into this. Why can we just move all of your volume over to checker right away, things like that, so there are still levers that they can pull. It's just not as immediate as signing a contract, and so oftentimes you have to start thinking about this like it's not an end of quarter thought. It's a beginning of quarter thought right around, how am I going to hit my target? What are the levers at my disposal? Like, how much do I have in pipe? Pipeline? Do I focus on closing more deals and the deals that I have in that stage, one bucket of pipeline, or do I focus on all the customers that I closed last quarter that still haven't gone live that told me they're going to go live this quarter? And so ultimately, it is thinking about it earlier and just thinking about like multiple levers, as opposed to just signing a contract, and
Sean Lane 30:22
so does the rep get paid anything on kind of what the expected volume is, or is it only once you see that volume come through? So
Lauren Davis 30:32
I have talked to a number of consumption based companies on how they comp sales reps, and transparently, what I've found is I don't think anyone feels like they have it like 100% figured out. I've talked to certain companies like every year when we kind of reset on compensation. And it is also interesting to see how those companies are like, still continuing to iterate, even like larger companies that you think have it like figured out, right? So it differs some companies will, do, you know, maybe it's majority revenue. So one thing that is fairly common is majority will be revenue, right? And is really just the size of the bucket. That is not around revenue. So some companies, it's 100% revenue, nothing else. Oftentimes you try and shorten that window as much as possible to make it a little bit more immediate and instant gratification. So maybe you comp them on revenue from their deals for the first six months, right? That really depends on how quickly these deals are going live and how quickly they are spending the bucket that the second bucket differs based on the company. So you might have like, 20 to 30% of someone's compensation coming from non revenue, whether that is just sheer number of deals closed or like new logo signed, whether that is based on a estimated bucket, whether it be like estimated annual contract value or the booking amount. I've also seen companies do it based on, it's what we call era, but companies will call it different things, but basically like the estimated revenue acquired, so based on the sales rep who sold it, based on the company firmographics, based on the number of background checks that we think they're going to run. What do we ultimately think that that will, from a data science perspective, result in, from a revenue perspective, as opposed to just holding Okay, the customer said they're going to run 100 checks, so we believe they're going to run 100 checks. We look at other variables to determine maybe it's only going to be 80, right? So I would say that second bucket really differs based on the company, and I've seen it transparently change year over year. When I when I talk to different companies, yeah,
Sean Lane 32:45
I love that you have, like this cohort, that you all kind of get back together every year and they're like, Okay, what's new this year? What are people trying? What didn't work the year before? I mean, that's the only way to do it. And so I very strongly believe that there will be more companies on models like yours than the typical SaaS as we continue to move forward, both because, you know, usage based and consumption based are becoming more popular, but also, like as more of these AI powered tools take over, like seat based models are just not going to work, right? They're just not there's gonna be more and more folks joining your cohort and looking for ways to do this better. And so as you look back on the number of years that you've gone through the planning cycles and the comp planning and everything that you've experienced like, what's the thing that you wish you hadn't done? What's the thing that other people listening can skip over and say, Man, like, skip this very painful mistake, because we're never gonna try that again.
Lauren Davis 33:48
I mean, the number one thing that comes to mind is paying people just on bookings, and maybe it's just because we were talking about comp. But, like, do not do that. It's one thing if it's a portion, but then you will run into inflation. So, like, it's basically saying, Hey, Sean, how much do you want to get paid this quarter? Right? Like,
Sean Lane 34:10
whatever you want for the deal,
Lauren Davis 34:14
absolutely. Like, do not do that if you choose to do it for a portion. Really think about guardrails and really think about how you'll manage the team, or things that you will checks and balances you will put in place to understand why, right? So whether that is, hey, they showed me proof that last year they ran 100 checks, or, you know, they used our, like, a similar product, this amount, those things are things I would take into account, but absolutely, like, not 100% of comp there. And my other thing I would just say is, like, reach out to people, right? So if anyone's listening to this and they want to talk about consumption world, like, I will gladly talk to them. I think, like I mentioned, there are certain people, certain companies I try and talk to consistently. Check in. I've also seen a number of like, more and more startups coming up to your point with this type of modeling. So that is also really interesting. But I think we're all still learning right, and there's certain areas that people have figured out or working enough, and also what works for one business might not work for another. I think that is, like, always true, but I think it's learning from other people and other people's mistakes, or what they've tried and again, going back to the earlier comment around, what other challenges did that present, right? So, like, maybe we did have it figured out. So for example, we moved entirely to revenue from a commission perspective, but then you're missing that bucket of, what can I do today to impact my comp, right? So like, then introducing another component around, like new logo signed or go lives, or, you know, whatever it is, like commitment to get them something kind of more immediate that they can directly impact. So learning from each other is just so incredibly important.
Sean Lane 36:09
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?
Lauren Davis 36:18
I mean, my favorite types of books to read are probably not great books, but like fiction, so I would say, I think the best book that I read this year, my favorite one that I read this year was Daisy Jones and the six I really, really loved that book. That's awesome. All right, the Amazon TV show, not as much, not
Sean Lane 36:37
as good. Okay, I've been recommended both. Like I'm O for two. So I gotta, I gotta, maybe start with the book. Yeah, book's Great. Favorite part about working in ops.
Lauren Davis 36:45
You get to see everything, and you get exposure into every single nook and cranny of the business, and really understanding, like how it works. You get exposure into every single type of person in the business, which I also find really fascinating. I also love what is very important to me. Like in a previous life, I thought I wanted to go into sales because I'm hyper competitive and I need to see my impact. Turns out, sales was informed me for a number of reasons, but what I love about Ops is that you directly see your impact. If you are in an ops role and you're like, I don't know why I'm doing what I'm doing or how that impacts the business. Like, let's talk, because that should absolutely not be the case.
Sean Lane 37:30
Flip Side, police. Favorite part about working in OPS,
Lauren Davis 37:32
there's always too much to do. I would say actually, like, it's not necessarily that there's too much to do. I think you could say that for a number of different roles. I think what is really challenging about Ops is you have so many different customers and different teams that you're working with. Like the greatest benefit is also the greatest weakness, right? You have so many different customers, so many different people to work with, and so prioritizing across those different teams, and then also communicating that back to make sure people understand. Right? There might be a quarter where you're not giving as much attention to a particular team because of the needs of the business and the priorities of the business, and that is okay. And so how do you build those relationships so that you can have those conversations and communicate and make sure that people understand? It's not because you are not as important. It's just because we only have so many resources, and we have to direct them here this quarter, for whatever reason,
Sean Lane 38:28
someone who impacted you getting to the job you have today. Matt
Lauren Davis 38:31
curl. He joined checker in early 2020, previously, we were decentralized. So we were in, you know, marketing offices and marketing sales ops. Was in sales etc. He joined in early 2020, and we centralized under REV ops. My background is historically in marketing operations, and I was really looking for a way to kind of break out of that. And I do think especially with Rev ops in particular, people tend to gravitate more towards sales ops background. I have a number of different thoughts there. I think it's important to have exposure into all of them, but I was really looking for that, and Matt was just great at really focusing in on individuals. What are their strengths, and how do I help? Like, advocate for them, and like, make sure that they have the visibility into that and exposure into that. So I'm very, very thankful one of him, like, letting me kind of move into the rev ops world and seeing something in me, but also bringing me along in a number of things. So he was, like, very much just like, let me overly communicate, let me be overly transparent, and just tell you all the things I'm thinking about, and also making mistakes along the way. I remember there was one day he was out and I made a decision on, like, sales comp. And he came back and was like, I wouldn't have made that decision, here's why, but like, it's okay. And you know what, like, two years later, it was still biting me in the ass, and I was like, Oh God, but I'll never make that mistake again.
Sean Lane 39:54
So that's awesome. Shout out, Matt. All right. Last one, one piece of advice for people who want to have your job. Up someday,
Lauren Davis 40:00
talk to people, listen, learn, be curious. I would say that's the number one thing. Be okay, stepping out of your comfort zone. I think the number one thing I see from people who say that they want to move into rev ops or out of a niche of ops, right? So going back to like I was in marketing ops, like moving out of that, people oftentimes will say that, but then gravitate towards what they know, which I totally get. And so making sure that you have enough opportunities where you put yourselves in that uncomfortable position, or at least are paying attention, right? So going back like I know, there's a million things going on all the time in OPS, the reason why rev Ops is so important is because we see the entire business right, and providing that context to our stakeholders, for them to understand, like, hey, actually, this is why this thing is really important, and this is all the different ways that it impacts the company, or vice versa. This thing, Mr. Customer, that you might care a lot about, will only have this small impact, right, as opposed to this other thing, right? Or, like the 8020 rule, like trying to put things into perspective. So I think it's incredibly important in rev ops to make sure that you are paying attention to areas that you might not think directly impact your area, but probably do. And I also think that that's the number one way that you will learn and get exposure and like realize how to take that next level in Redbox.
Sean Lane 41:36
Thanks so much to Lauren for joining us on this week's episode of operations and special. Thanks to dv for making the intro to Lauren in the first place. If you like what you heard today, make sure you subscribe to our show so you get a new episode every other Friday directly into your feed. If you prefer YouTube, you can also subscribe to our YouTube channel operations with Sean lane. If you learned something today from Lauren or from any of our guests in the past, make sure you leave us a review on Apple, podcasts, on YouTube, wherever you are consuming this show, more reviews really help more folks to find the show. All right, that's gonna do it for me. Thanks so much for listening. We'll see you next time this episode of operations was presented by Tiger eye, data security is a leading concern for modern B to B, and Tigray is built with data privacy at the center of everything they do, each customer's data resides in a single tenant, private cloud with AI trained exclusively on data sourced from your business. Every change to your CRM is captured and easily accessible in whatever form you need them to learn more, schedule a personalized [email protected] you
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