Digital: Disrupted: Avoid the Trap of Revenue Leak

Episode Transcript:

Paul Muller: Well, today we're going to talk about something that should be a concern to all of us as businesspeople, really no matter what our roles are, and that's the issue of an accurate sales forecast. Now, wait, before you flip to your next podcast, hear me out on this. In my opinion, and I don't think I'm alone, crappy demand forecasting is the root of most of the evils we face today. Okay? Evils might be overstating it, but whether it's the hoarding of resources by people who think they need more than they do because they've overestimated demand, or people who've run out of stock because someone didn't tell them in manufacturing just how hot the next brand new product was going to be with customers.

Virtually every other function in a business gets impacted when demand forecasting goes wrong. The most recent round of Silicon Valley layoffs is just one example of how much of an impact this can have on everyone's lives.

But if you've been around salespeople as long as I have, you know that accurate sales forecasting is right up there with solving world peace and famine. It’s no surprise then to discover that revenue operations was the fastest growing role according to LinkedIn's most recent study and today's guest. But before we get into the topic of how to improve revenue forecasting, I'd love you to check out rocketsoftware.com to see why over 10 million IT professionals rely on them every day to run their most critical business applications, processes, and data, their digital disrupted right from the start. And we thank them for their support. Everyone, welcome to Digital Disrupted. I'm your host, Paul Muller. And today's guest trained as an economist, has co-founded and driven businesses over 30 years including roles in sales, marketing, and of course business leadership. He's most recently taken on a new role as CEO and co-founder of Clari. Please welcome to Digital Disrupted, Andy Byrne. Hey, Andy.

Andy Byrne: Hey, great to be here. Thanks for having me. Appreciate it.

Paul Muller: Great to have you. How did you feel about that introduction?

Andy Byrne: I thought it was perfect. I thought it had enough emotion that resonates with most of our customers.

Paul Muller: Excellent. I'm pleased to hear it. I mean, I don't think I'm overstating it, but before we jump into the topic of, I guess revenue forecast, revenue leakage and managing that process, we do a little thing on the DD we like to call the lightning round. Are you ready to have a crack?

Andy Byrne: Sure, I'm ready to go. Let's do it.

Paul Muller: Do it.

Paul Muller: Yeah, it's like let's do the big wrestling voice. Alright. First up Andy, what would people say is your superpower?

Andy Byrne: Superpower? It's evolved. I'd say superpower would probably be empower, helping people realize their fullest potential.

Paul Muller: Nice. I'll take that. The most disruptive technology of all time?

Andy Byrne: Well, I'm going to go with my favorite disruption, which is aviation and air travel. I love how it's transformed the world. Every time I see an airplane flying in and out of any airport that I'm in, and I'm in a lot of them, just to be able to see the world and have people get together, I think that's the most disruptive and powerful tech.

Paul Muller: Wilbur and Orville. The best quality a leader can have?

Andy Byrne: I think the most obvious choice that people would say is empathy. But I'm going to go maybe a little unorthodox and I'm going to use the word intentionality, being intentional.

Paul Muller: Say more, say more.

Andy Byrne: I think a lot of leaders don't realize that a lot of leadership moments are situational. Do I work the problem? Or do I work the team? Thank you Bill Campbell, do I lead from the front as a role model, or do I lead from behind and facilitate? Does this coaching moment ask me to coach for performance or coach for development? And then finally, I'd say that my one moment I always bring up to young leaders in my leadership courses is when you look at your calendar, you don't see meetings. You see moments to inspire who is your audience, what do they want to hear? How do you open, how do you close? I think that is a quality of leadership that's being intentional given the situation that is not really trained across leaders in business.

Paul Muller: There's almost a whole podcast in that. That is a brilliant answer. Thank you Andy. Your advice to people starting their career?

Andy Byrne: My advice is really simple and it's consistent and I'm pounding it into my two young boys that are trying to get internships. They're both 19 and 20. Two things. One, curiosity, two, tenacity. That is it. You have those two things, and you check yourself at the end of every day, every week, every month, every quarter, every year. And you measure your level of curiosity and tenacity and you, if it's off the charts and you've done everything you can in those two buckets, you will have a profound career.

Paul Muller: Brilliant answer. Slight change attack. The first thought that comes to mind when you think about demand forecasting?

Andy Byrne: Well, there's all kinds of forecasting in the company. This is the one thing that I want to make sure that lands with your audience is that there's forecasting on ARR, there's forecasting on revenue, there's forecasting on demand, there's supply chain. And it rolls up to what all these companies are trying to do, Paul, and that is to be able to run revenue and forecasting is a component of that. So, if you rise up and you think about the number one most important business process in the company, it's revenue. No one can argue that. And it happens to be the most antiquated system that's run in poorly designed systems to run demand forecasting, bookings, forecasts, etc. And that was the massive opportunity we saw hiding in plain sight when we started the company.

Paul Muller: We're going to get into that in just one second. We've got one more question to go. If you could use technology to solve one world problem, what would it be and why?

Andy Byrne: I kind of have a trifecta. I think mental health and drug addiction would be just profound. It's all over the world. And then you'd have a byproduct of being able to solve for homelessness. I would love to see technology that can solve those three dimensions.

Paul Muller: Yeah, well something to work on for sure. They’re big problems. Hey, speaking of some of the challenges that ail our world and some of these are more pronounced in others where do we find you today?

Andy Byrne: I'm at home working away in my home office.

Paul Muller: And where are you based out of?

Andy Byrne: I'm in the Bay Area.

Paul Muller: Oh, got it. Okay. I guess some of these issues like homelessness and so forth are definitely problems out in that part of the world as they are for sure in many. So, tell us a little bit about your background. How did you come to find yourself realizing that the revenue leakage and management of all of the, as we talked about, related disciplines were as you say, this problem hiding in plain sight?

Andy Byrne: I guess I'd say two words, Paul, scar tissue. Been 30 years in and around the revenue process last decade of my life, it's been my professional responsibility to help CEOs and boards answer the most important question in business. Will they meet, beat, or miss on revenue? And for me, next to my job as a parent and my job as a family member, honestly it's the most important job I've ever held in my career. Helping great companies like Adobe, PerkinElmer, Allied Bank, MongoDB, Sodexo. Helping them realize their fullest potential. We do that by really helping them look at how they run revenue, transforming it and the results are significant— more efficiency, more growth, more predictability. And for me it's a very compelling and rewarding journey. I'm pretty grateful and hopefully we help more great companies realize they're fullest potential and we can build our own great company in Clari.

Paul Muller: Yeah, I love it. So, let's talk a little bit about this. I feel like even as we open up, we might be coming at this from slightly different perspectives and that's okay because I guess meeting each other in the middle is really important. I see revenue operations, chief revenue officer those sorts of related titles. And as LinkedIn would say, it's one of the fastest growing jobs on LinkedIn, the US Bureau of Labor Statistics can disagree with that, but that's totally cool. I see those as synonyms for basically being related to sales and the sales function. Maybe that's incorrect. And I see sales, and this is again, I sort of have a customer-centric view of the world. I see sales and revenue being a function of demand because I have a point of view that buyers buy, sellers don't sell, right? You can't sell something to someone who literally doesn't want it. Unless there's demand there, you are going to have a problem, right? I guess number one is have I gotten that wrong? I kind of got the impression based on some of your opening that maybe I've misunderstood that.

Andy Byrne: Well, a couple things come to mind. Do you trust the US Bureau of Labor or more modern systems?

Paul Muller: I was actually going to divert on that very topic because one of the things that I thought was interesting, just to give you a quick sense of what the BLS thinks of the top growing jobs in the United States— nurses, wind turbine techs and ushers, believe it or not. And as I was looking at some of that data yesterday, I thought to myself, has the BLS got it totally wrong and is LinkedIn a more high-fidelity indicator of what's happening? Or do we have this sort of two speed economy where the knowledge worker world is sort of glommed into LinkedIn and there's almost this sort of anachronistic data set and view that is the traditional economy in inverted commerce? Sorry, maybe again, I don't want to divert too much.

Andy Byrne: No, no, I think it's an interesting diversion. I'll just make one comment on it. It's very similar to how we track consumer confidence. You look at the organizations that do that today, they've got manual, they've got human beings that are sitting out in front of grocery stores and they're analyzing on that and trying to roll it up into a spreadsheet. Why aren't we analyzing data from Amazon? data off of all of these commerce sites and getting it in real time? So, there's definitely your point about there's two different systems analyzing data in two different economies for sure. No question. Anyway, back to your commentary about demand forecasting, I think we're aligned. I wanted to make sure that your readers understood that demand forecasting is one element of how you run revenue. If you think about revenue as a funnel where we've got marketing, we've got sales, and they have an integrated process of creating the demand, converting the demand, and making sure you can close that demand, then that is going to drive a demand forecast. But there's all kinds of forecasting whether how much pipeline we create, our assumptions on how we're going to convert that, the attainment of the salespeople all the way to, okay, what is in the case of PerkinElmer, they need to rely on their supply chain forecasts or relying on what the CRO is committing in their forecast. And there's a downstream trickle effect that goes across the entire funnel and you need a system to run it end to end. And there's never been anything like that.

Paul Muller: Yeah, look, I couldn't agree with you more. And one of the great challenges I have as a business leader every day, and this is why I do sort of tend to think of it as demand forecasting because if I understand what's coming, let's call it revenue forecasting, then revenue, there was a function of the widgets I produce or the work that I do, the services I deliver, and those require resources to deliver them. Unless I'm fortunate enough to be running a software company and just printing the next license off. And my point is that there's usually goods or services people that need to go into that. And there's nothing worse than going, wow, we've just had a bumper set of sales that I didn't see coming and I cannot deliver what needs to be done because I haven't anticipated this because my sales guys got it wrong, or my marketing team got it wrong.

Andy Byrne: By the way, Paul, all of those different constituents, finance, sales, marketing, historically, they've been in different systems.

Paul Muller: I was going to ask you what's wrong with the process today? Because I mean, it's not for lack of technology. We've had CRM come in and say it was going to be the silver bullet. We've had business intelligence tools, Tableau, I've had it up the wazoo. And inevitably in my 30 years of doing this, I find myself back in Excel doing like Kung Fu with Excel. What's been your experience?

Andy Byrne: Well, I'd say that my experiences still, it's just fascinating because 10 years ago, the thesis I took to Sequoia Capital was that there's never been a system purpose-built to run revenue. And I explained to the partnership there that CRM, Excel spreadsheets and BI tools are the way they run it. Our customers call it the three-headed hydra. And these are systems that were designed 30 years ago that were more general purpose. And we saw that entrepreneurs— they see things that others do not see— saw that they were posing a real threat to companies’ ability to generate revenue. And we, as a result, there was revenue leak happening that we started to see across the entire revenue engine in every single company on the planet. And that was the aha and why we felt like we have to build this company.

Paul Muller: Talk to me about what's going wrong with the revenue management process today as you've seen it. Maybe just give us a couple of examples of what are some of maybe the things that people think they're doing but are in fact not helping them get to where they're needing to be in terms of getting some fidelity on that. As you say, it's really simple. Are you going to meet, beat, or miss? Because it's not for lack of people, right? Because there tends to be people thrown at this problem all day long. So, what's the fundamental thing we're getting wrong with this?

Andy Byrne: Well, let me, instead of opining my opinion, why don't I just tell you what happens? Why don't I just tell you what happens inside customer accounts? We've done over 5,000 deployments now. What happens is a customer is trying to use the CRM, which is general purpose built for a lot of different functions. It started in sales and then they started to just say, okay, there's all these different from commerce and from different sort of ways and different business processes. And the thing that's been really, really powerful about the CRM is it's so flexible in general purpose, great industry has been built off of it. What happens when these revenue professionals are trying to use the CRM to run revenue is that they end up exporting a lot of the data into Excel spreadsheets. I'm going to go street level for you here, Paul, because the rep needs to analyze their accounts in a certain way that's different.

And the CRM can't do it. The frontline manager that's above that rep needs to manage their book of business differently. The regional director, the GO lead all the way up to the CRO and that's led to the proverbial Excel hell that you mentioned. That's from the rep all the way up to the boardroom and it cascades into marketing, cascades into finance. So, you have CRM, poorly designed, general purpose, you got Excel. Then what happens, Excel breaks when you're trying to aggregate data and to try to figure out what happened in the past, what's happening in the present and how do we predict the future. They go into BI and they're exporting data into BI. And so, this is what's wrong is that it's not the customer's fault. It's not the revenue team's fault, it's not sales’ fault. It's that they're forced to live in these antiquated systems, and they can't collaborate in one system. They're all over in different points of view that is causing revenue leak to occur throughout the entire funnel. There are leads that don't get followed up on, there's targets that go stale, there's opportunities that slip and they didn't even know why they slipped. There are deals that close and they don't even know why they close. They're the end of the quarter, it's after the fact. And this is an antiquated, reactive system. And unfortunately, that's how they run revenue today and it's profoundly challenging. Does that help?

Paul Muller: It helps a lot, and it literally sounds like a lot of my life, both the good bits and the bad bit, but the Excel hell bit feels familiar because of course as part of that process, there's what I'd call the judge. So at least in my old world it would be, you got handed a forecast or you got handed an estimate by your sales team, you'd then kind of look at them all and go, yeah, Johnny's a bit optimistic, Jennifer's a bit conservative. Jason's somewhere in between. I'll kind of have to add my little wet finger to it and go, I think they're going to actually come in here despite what they've told me they're going to do, which I guess is the pre-digital disruption version of AI was I'd use actual intelligence, but I'd have to make a judge. And then of course my boss would make a judge on me, and they were aggregating four or five different sales managers. And it went up the tree and you kind of wound up with all of this human judgment up and down the tree. As you say, a lot of them were just looking at Excel spreadsheets and just had to take their best guess. It definitely seemed anything but optimized.

Andy Byrne: Yeah, no, I just think one thing that is really interesting on this— If you think about everything that you're talking about, the word that we find that's being used quite often and the theme that is cascading from boardrooms is revenue collaboration. If you think about what we're all trying to do. Companies are trying to get all of their revenue critical employees, and they're not just in sales, right? Revenue is the most collaborative business process and any company on the planet touches marketing and pre-sales, finance and post-sales. And they're trying to get them all into one system so they can collaborate. And in a lot of companies, over half their employee base are revenue critical. That is, they perform some sort of function that's going to impact the company's ability to generate revenue, yet they're in different systems. The rise up commentary is they need a system by which all their revenue critical employees can collaborate and run revenue and get out of these old antiquated systems. If they do that, that's eliminating friction, that's driving collaboration that allows them to be in an outperformed situation where companies like our customers, Alteryx, had a great quarter and crushed it and we’re a big reason why they did that. So that's another reason why revenue collaboration is important and it's a big topic that's being discussed.

Paul Muller: Yeah, no doubt. I wanted to touch on the term you've used twice now that our listeners may not be familiar with. And that's revenue leak or revenue leakage. What does that term mean and how big a problem is it?

Andy Byrne: What I'd say is instead of me talking about it, I'll just tell you what other people are saying, so Boston Consulting Group was analyzing revenue leak. Let me first make sure everyone understands what revenue leak is. Revenue leak is the revenue that a company has already earned, but has yet to capture. Let me say that again. The revenue that your company has already earned, but has yet to capture. What happens is every company that has achieved product market fit, Paul, and go to market fit. They've got some sort of flywheel in both. What do they do? They hire a revenue leader. That revenue leader comes in, they build their engine, and they build a team, and they partner with marketing, and they have their revenue engine and it's leaking all over the place and they don't know where the leaks are happening and the leaks are profound. Our own data suggests that up to 15% of company's revenue is lost due to revenue leak. And another stat for your readers, Boston Consulting Group did a big survey and the readout of it was up to $2 trillion worth of economic devastation is happening every year due to revenue leak. It's a big topic that people are talking about and it's pervasive and it's happening everywhere in every company.

Paul Muller: I'm curious what you mean by, because you did pause for effect, I've earned it, but basically I haven't booked it. What does that mean?

Andy Byrne: Well, if you think about what's happened, when I talk about product market fit and go to market fit, there's demand for your company. It's out there, you just have to go get it. And then once you get it, if you're a student of revenue, what happens is you build a funnel, you have initial intent, and then you increase the intent and you increase the propensity for that person to want to buy. And there is an engine that's being built to be able to capture that demand because it's already out there and be able to easily convert that demand with the least amount of leak that leads a company to be able to have what we call total revenue precision, which is a company's ability to predictably and repeatedly have the maximum amount of revenue every 90 days—being in a beat and raise cadence.

Paul Muller: Let's talk a little bit then about the role that technology plays in this, because I guess one of the things— we talked a little bit about me using actual intelligence or human intelligence— let's call it that rather than artificial intelligence because you've probably been in a sales environment where a sales manager is the sort of sales manager who's cajoling or a marketing manager for that matter. Sunshine Pump, right? Wants to cajole the sales team into forecasting a little bit more aggressively than maybe they should be under the circumstances. And this is a team that's sort of notorious for missing or maybe boom and bust. They'd have some great quarters where they were on target and they'd have, they were wildly off. You've got some salespeople who, because they're being inspected, tend to fill their pipeline with opportunities that are just going to take forever to close.

Sometimes you're selling stuff that's got a really long sales cycle mixed in with things that got a short sales cycle. I mean, all of these things taken individually make the process of revenue management challenging, aggregated across a global business with different cultures, different behaviors, partners in the mix, et cetera. It becomes really, it's a complex problem. What role can things like technology and artificial intelligence do you think play in helping to see patterns or maybe actually better still to not see patterns where maybe humans are interpreting something that's not really there, but maybe detecting some of that underlying capability. How much has the technology, I guess, helped improve the fidelity of some of those numbers?

Andy Byrne: Well, you've asked a lot. You've said a lot on that. If I was to summarize, I would say the original question of how technology has impacted the ability for companies to run revenue nowadays, if I rise up and I think about the big buckets, there's data of which we have so much more access to really, really interesting sets of data. There is the ability to take different types of data and correlate it and you know, have to normalize the data and you have to actually do correlation. And then there's predicting. I'll take each one of those in turn and I'll try to address some of your specific commentary. So, on the data side, we now have such rich access to all of the behavior data that's going on from emails that are going back and forth, contracts, relationships that are being set up, the actual conversations, the actual language that's happening.

And you can look at the human judgment and the machine is sitting alongside in the pocket of these humans, whether it's a rep, a manager, exec, and they're able to look at so much more signal that a human couldn't see. And now that this machine can start to pattern match on data that they're seeing, because if you take a look at, just to dumb it down for your audience, a deal that was closed won, a deal that was closed, lost. Let's look at all of the patterns of all the data about when did they call? When did they hit the website? who did they talk to? Were they single threaded, multi-threaded? what was said? what was not said? What type of firmographic, technographic, demographic data were we dealing with? We can harvest it all. So that's powerful, where machine learning can actually work alongside the human to do two things.

One, identify risk, two, identify hidden opportunities that we're not aware of. Okay, your point about different cultures, different geos, that gets to pattern matching and being able to look at using machine learning that can look at different clusters, what they use in AI vernacular and say, okay, well this is a cluster of data that I'm analyzing from. This is from this product line, this is from this actual person. And utilizing this type of pattern matching to further increase the accuracy of what that machine might deduce is a risk or an opportunity in driving revenue. And then as you scale that out, what happens is this technology now using large scale data, being able to apply machine learning, do pattern matching, can now start to answer the most important question in business are you going to meet beat or miss in revenue? And that's on every dimension, pipeline you're going to create this quarter, next quarter deals, you're going to churn revenue that you're going to land what you're going to need for your supply chain.

And so, we're still in the early innings of this. I don't want to oversell that it's going to be, it's all perfect and it works perfectly. It's still very early, but we're seeing profound change that drives three dimensions of value, efficiency, growth, predictability, and it's the number one most important business process in the company. And so that's why you're seeing job growth in revenue operations being the most important job, the fastest growing job in America is in large part because, A, the technology is there. B, there's real value being delivered based on the tech. And C, it's the number one topic in the boardroom. And the boards are driving the CEOs to have a conversation that's a directive and partnership between the CRO and the CIO of how do we do revenue collaboration and revenue governance across the entire end-to-end revenue process. And that's the movement that's happening.

Paul Muller: No, it's fabulous and I think it makes a ton of sense, as I said, but it marries well with my own experience in some of the challenges of doing this. And all I can say is I wish I had had this in my tool belt 15, 10, 20 years ago.

Andy Byrne: You and me both.

Paul Muller: Yeah, absolutely. Looking forward then how much, and again, I'm asking you to maybe longitudinally across your existing client base to give us a sense of this, is there a quantum, a band of improvement in accuracy that you've seen as, or you've had reported back to you as people have looked at what impact this kind of technology process improvement can have?

Andy Byrne: Yeah, this is the thing I'm probably most proud of in that a lot of value propositions are hyperbole or they're not grounded in reality. And what's really powerful about this, not really, I can give you our data, but I don't want to oversell on this pod. What I want people to realize is that deploying purpose-built technology to run revenue, you're going to get profound impact that you can go to your CFO and say, pre-Clari post-Clari, our data is the following. On average across a thousand plus customers, we've been able to increase their conversion rates north of 12%, reduce their slip rates by north of 15%, and Forrester did a total economic impact report on it that we have increased rep productivity by 80%. Now seeing is believing, it's one thing to talk about the value engineering and what is the actual ROI. But to me, if I would say anecdotally, what I'm most proud of is I just had calls with three CEOs this morning, different ones publicly traded, one's a pre IPO, and one is running about 35 million in revenue, just finished their series C, all three CEOs, have said “Andy, the technology that we've deployed has been transformative in terms of how we think about running revenue.”

And what I can say is that it's really important for boards, for CEOs to really take a deep look because especially in this environment, every drop of revenue matters and that's why you're seeing a lot of investment and a lot of job growth in this area.

Paul Muller: Hey, I've got a couple more questions if you've got a few more minutes for me. They're related and it's about the practicalities of implementation. First one size of organization. Obviously these tools tend to get better. The more data you throw through them, the more longitudinal that is. The longer period of time you've got, I'm guessing the more compares you can do. How big an organization, how much, what sort of sales volume do you need before these tools become practical? I mean, is there a lower limit to how big you can be before you can start to implement this sort of technology?

Andy Byrne: A great question. I really like to answer this one because I thought it was going to be just for big companies.

Paul Muller: Yeah, me too.

Andy Byrne: And when we started, we were closing companies like HP, Adobe, and what happened is we started to see this flywheel effect after we got to about 250 customers. We started to see these CROs who are part of publicly traded companies graduate back to series A, series B, series C companies. And it's the first thing they buy—first thing. And it's not just because of predicting, it's about how you run revenue. How do you make sure the reps have an interface that changes their life, that allows them to close deals faster? How do you give the managers a new interface that allows them to drive more revenue? And then how do we help those CROs, and those boards predict where they're going to land? Now, to your specific question on data, what I found interesting is we need about six weeks' worth of data to start to extrapolate where we think things are going to land.

Where we get north of 90% accuracy is when we're working on about two quarters worth of data. After we get beyond that, our accuracy is in the high nineties after about four to eight quarters worth of data. So, it does have to learn over time. I want to be very direct about that. But the thing I'll also say for the listeners is not, I always say this to the CROs, it's not about is Clari 99.999% accurate? The way to use machine learning is, it's going to, in many use cases at the rep, manager, exec, RD level, it's going to smoke out issues that you didn't consider when you were running your one-on-one, when you were running a pipeline creation meeting, when you were running a forecast call. And what that does is it's acting as a chief of staff that's tracking either areas that are leverage areas that you didn't think about or areas that are risk. And in that regard, sometimes we're not, right? Sometimes the AI's not right. But a lot of times we get back from the CROs at these small companies that it's been just transformative, allowing them to just simplify how they run revenue.

Paul Muller: Yeah, I mean, again, I can see this. I've been I mean literally could spend hours with you talking about the number of pipeline and sales reviews and revenue obviously tied to submitting an end of quarter forecast where in hindsight, some behaviors that should have jumped out as problems didn't until a post-mortem. And you don't want to be doing post-mortems, right? That's the emphasis on the word there is the dead bit. You want to be catching that ahead of time and asking smart questions. A lot of this is about knowing what questions to ask, isn't it?

Andy Byrne: And Paul, can I just say if we rewind and you just actually wrote the language down that you just articulated and you really think about the words, it's really about collaborating and it's really about governance. How do we control it? What people want to do is they want to make sure that everybody's collaborating in one single source of truth. And these CROs that even go back to these smaller companies, they want to govern or control the revenue process. You think about what these companies are trying to do, they're trying to control accountability, discipline, behaviors and outcomes is how I think about it. And I teach this all the time. And if they can do that, if they can govern the revenue process, they can very easily implement what the public markets like to see, which is a beat and raise revenue cadence, and they get predictability and they get precision, and everybody wins when that happens. That drives more opportunities. Our customers win, their employees win because they're in a beat and raise cadence, shareholders win. It can have a profound impact, if that makes sense.

Paul Muller: That absolutely does. Second to last question on this before we wrap up with next steps. You mentioned, we've talked about CRM, sorry for people listening, customer relationship management systems right up there with enterprise resource planning as and for that matter, business intelligence projects as projects that sort of very frequently in organizations metastasize into these multi-year things consume millions of dollars, never end, not always associated with rapid success. You've talked about governance, behavioral change. Again, these are some of the gnarliest problems in business. Again, you probably anticipate where the question's going. How roughly how long a timeframe are we looking to be able to implement this sort of thing given it's tied to so many of the gnarliest problems we face in business?

Andy Byrne: Okay, I love this question. A couple things come to mind. One, I just want to call out what I thought was profound. One of our customers said, hey, the R in CRM is not revenue, and the R in ERP is not revenue either, has never been a system purpose built from the ground up. So that's point one. Point two, when I started the company, this is something I'm very proud of. I remember saying to my co-founders that I don't want to create a company that for every dollar of ARR that you need to spend, it requires $4 of SOW. That it's going to require this big heavy lift professional services project. So, for our platform, it literally is up and running same day. And you can start to send, we do this, we do a revenue leak assessment, we bring it in, we show CEOs and CROs, they say, oh my gosh, I had no idea.

Now that the key thing is that as the lift is in deploying the interface to reps, to managers, to execs, because it's a new system and to enable them to make sure that, because change management does happen, no doubt about it. But what we do is we actually start with deploying our conversational intelligence technology called Wingman, and that is up and running same day. And we can deploy the full platform same day. But to get to where I go with this to simplify for the audience is there's time to go live. Time to wow and then time to value and time to value at scale. Four different points. Time to go live, I said already it's less than a day. For us is same day, time to value takes time because you got to deploy to a work group, you got to get feedback from them.

They say, yes, the rep says, please don't take this away. Manager says, this is transformative. Boards are seeing that Clari is now running all of the forecasting and Clari is in the boardroom, but then to get, and that takes roughly about, and it's not about the configuring, the software is just about training people. That takes about two weeks and then to get across 5,000, 10,000 users can take in order of less than a quarter is kind of the way it rolls. And that's a function of they got a sales kickoff, they got QBRs, and we launch off of those, if that makes sense. So that's the real-world story of how you roll out.

Paul Muller: That's exciting stuff. And I do like the intentionality back to use one of your opening words about designing a capability that doesn't require a lot of bodies to implement it. Because yeah, that has almost always been the greatest inhibitor to scaling and frankly, speed to outcome, time to outcome.

Andy Byrne: I would say that Paul, I've felt that pain and I just didn't want it. I didn't want to serve that on my customers because that's what CRM and ERP does and it's painful.

Paul Muller: We're all grateful to you. I've got to be honest with you, that's been one of my great bug bears of the tech industry is that this one comes with a human. Alright, if people are interested in learning more about the topic of revenue management, of revenue leakage, of collaborating around revenue, where can they go to learn more on the topic?

Andy Byrne: Yeah, I mean, what I would say is that they should go to my LinkedIn. They should subscribe to both LinkedIn and to the Clari posts that are there. That's where we are sharing most of our learnings. There is clari.com. Obviously they can go there as well.

Paul Muller: Awesome. Well thank you for that. Hey, last question for you. The show sponsor, rocket Software, big shout out to Rocket, they've got a set of values that they talk about that matter to them, empathy, humanity, trust and love. Just curious, Andy doesn't need to be any of those four. What matters do you do right now?

Andy Byrne: What matters to me right now? Well, it's hard not to pick love because it's Valentine's Day.

Paul Muller: I'll take that answer.

Andy Byrne: Yeah, yeah. I don't really have the— I would say it's love.

Paul Muller: I'm going to go with love. Love is a good one. It's one of my favorite values for a company, a tech company to have love as a value I think is a huge thing and really a brave oven. It's very cool. Alright. With that, I want to thank you so much for joining us, Andy. I appreciate you taking time out of your busy schedule to meet with us and thanks again to Rocket Software for bringing us another episode of Digital Disrupted. Thank you all for, I'll use an anachronism tuning in. I know you're listening, you don't tune anymore, there's no radio involved. If you like what you've heard, do give us a thumbs up on whatever pod catcher you happen to be listening on. We'd really appreciate it. You can also reach out to me on Twitter @XtheStreams, our show sponsor @Rocket on Twitter as well. We don't have a Mastadon yet. Really got to set that up. So, if you've got any questions for our guests or ideas or topics you would like to hear covered on future episodes, we'd love to hear from you. With that, we'll see you all next week. We won't see you. It's a podcast, Paul. Stay disruptive. Everyone.