Justin Shriber joined BoostUp as the new CEO! Read "Letter From the CEO"

Groundbreaking Forecast Maturity Research for RevOps

In this webinar, Ben Schafer from Udemy gives practical applications and examples of how Udemy matured their forecasting processes and strategy, and our partner Matt Volm, founder of the RevOps CoOp, draws from his vast community’s experience to show why modeling for maturity in forecasting is critical for 2024 planning. 

Host

Aaron Janmohamed

VP of Marketing | BoostUp.ai

Guest

Matthew Volm

CEO | RevOps Co-op

Guest

Jeff Saenger

VP Customer Success @ BoostUp

Guest

Ben Schafer

Manager, Global Sales Ops @ Udemy

Key takeaways from this Mastering RevOps Webinar

Role of AI and predictive tools

The panel explored how AI and predictive tools play a significant role in improving data precision and forecast reliability. They discussed the transformative impact these technologies have on analyzing trends and making more accurate predictions, underlining their growing importance in revenue operations.

Increasing forecast accuracy

The webinar underlined the direct link between consistent sales processes and improved forecast accuracy. By following a structured approach, businesses can better predict outcomes, leading to more reliable forecasting. This connection demonstrates the importance of process discipline in achieving accurate sales projections.

Real-world Application for Udemy

Insights from Udemy's experience provided a practical perspective on evolving through different stages of forecasting maturity. Udemy's journey from basic processes to advanced forecasting methods showcased the tangible benefits of developing and refining forecasting strategies in a real-world setting.

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About this webinar

The "Groundbreaking Forecast Maturity Research for RevOps" webinar, featuring experts from BoostUp, RevOps Co-op, and Udemy, delved into advanced forecasting methodologies within revenue operations.

 

The webinar began with an overview of the extensive research undertaken over four years, culminating in valuable insights into forecast maturity. Key topics included the significance of RevOps platforms, the evolution of sales processes, and the integration of AI and predictive tools in enhancing forecast accuracy.

Real-world applications were highlighted through Udemy's journey, illustrating the transformative impact of structured forecasting on operational efficiency.

 

The panelists discussed how RevOps tools could provide leaders control over sales and operations, emphasizing visibility, alignment, and automation. Additionally, the webinar explored the dynamics of sales process adherence and its correlation to forecast accuracy, underscoring the role of discipline and consistency in achieving reliable sales projections.

 

The session also emphasized the need for foundational elements and appropriate tools in scaling organizations. Through practical examples and shared experiences, the webinar provided a comprehensive view of how businesses could leverage RevOps strategies and tools to improve forecast accuracy, enhance operational efficiency, and drive revenue growth.

 

FULL TRANSCRIPT

 

[00:00:00] So thank you for joining this webinar. This is the, uh, awesome research on forecast maturity for RevOps. This is the product of maybe four years of work directly with clients and pulling data religiously for about six months. And we've come away with some really awesome insights. But I will say just before we do introductions that one, everything you hear today is going to be obviously recorded.

We'll share it with you after this, but next month, we're actually going to be unveiling the actual report with a lot more detail and a lot more data. Um, we simply can't go over it live on a on a webinar call, but it's worth the read, and we'll send that across to everyone that registered for this webinar.

It's really good insight. We've already started field testing this with customers and prospects. And by field testing, I mean, we're going through this forecast maturity curve, the modeling, the frameworks, the best practices with customers, and we're seeing incredible results. And we'll talk a little bit about one of our customers today.

We're not going to make this a boost up [00:01:00] centric theme, though. This is really about the thought leadership and it. Helping to elevate teams that are trying to improve the way that they forecast, improve their process and alignment. We'll reference some of the studies that we've been doing. So, um, I'm just really excited about, about everything.

Um, Uh, just to kick things off, I don't know that we necessarily do a very good job of letting people know who we are. I mean, a lot of you have come in for the 1st time engaging with the webinar because hopefully the topic is interesting to you. But, um, let me take 20 seconds and just introduce boost up as, um, as a platform.

We call it the revenue command center really for forecasting and pipeline management. And really what we're after is. Giving leaders on the sales side and on the op side control over their processes, control through visibility, control through alignment, um, and process and automation. There's a heavy component, a module of AI features that, uh, that help customers identify risks and, and project more accurately their pipeline, the deals, their forecasts.

It [00:02:00] really comes down to getting control around forecasting pipeline management. So if you're interested, I'll send this link out. You can watch a demo on demand, or if you want to talk with one of our reps, you can certainly do that. But that gives you a little bit of background on who we are before we jump into it.

I figured it would be helpful for everyone to know who we got on the bridge. I can go back. Oh, I can't. Um, so, well, let's just hang on this screen for just a moment. Um, my name is Aaron John Muhammad. I lead marketing here at boost up more importantly, though, are the panelists that we've got here. I'll start with Matt cause you're on my screen left to right, Matt, who are you and what do you represent?

Uh, hey everyone. Uh, my name is Matt Ball. I'm the CEO and co founder of RevOps Co op, a global community of 11, 000 plus RevOps folks from all across the globe. Uh, you learn more about our community at revopscoop. com. And so I'm here, uh, because big fan of BoostUp and Aaron. And, uh, obviously have kind of a, a perch, uh, to [00:03:00] see all the things that people are talking about when it comes to forecasting problems, questions, uh, pipeline management, um, related topics that pop up in our Slack group and elsewhere, so, uh, able to bring kind of the high level.

Industry, uh, uh, kind of perspective, uh, to the table. Um, but really most of that expertise just comes from what I hear from smart people like Ben, um, and other people. So, um, I just kind of regurgitate the things I see and hear from, uh, from them. But Ben's the real. The real genius that we've got here. That was an amazing transition and set up for bad.

Don't mind introducing yourself. I don't think I need to say anything else after that. My name is Ben Schaefer. I'm on the sales ops team here at you to me for people who don't know you to me, you to me business helps companies achieve critical business outcomes and stay competitive by offering.

Engaging on demand, immersive and cohort based learning. Um, so we help companies and [00:04:00] individuals evolve and grow their competitiveness and capabilities in a fast changing skills based economy. Um, me being on the sales ops team, um, full transparency, we are a boost up customer. Um, and, uh, yeah, I think I'll be able to talk a little bit about how we've leveraged some of the framework that they'll be talking about to, um, achieve some business success over the last several years.

Perfect. And last but not least, a, uh, what do we call you? A homegrown maestro. Um, Jeff. Maestro. You can call me what you like, Aaron, but, uh, I'm Jeff Sanger, everybody. I run, uh, customer success at BoostUp. And I've had the pleasure of working with a lot of companies, um, helping them think about forecasting and what it takes for them to be successful.

And, uh, some of that has made it into the maturity models that we're going to discuss today. So looking forward to it. Awesome. Let's get into it. Um, so I'll turn it over to you, Jeff. And the way that we'll structure this is we, we do want to go [00:05:00] over. There's quite a bit to go over. Actually, it's a little bit of a change from previous webinars, but there's a heavy amount of information, data and, and, and, um, insights that we're going to expose to you.

Again, all of this will be shared with you afterwards, along with the report that we're going to be publishing next month, which includes everything. Um, and a lot more data, but please jump in the chat bar with any questions that you have. I'll rudely interrupt the panelists to try to answer your questions as best I can.

Then we'll we'll proceed from there. So go ahead, Jeff. Thanks, Aaron. So let's get started. So the revenue maturity models are bootsteps point of view developed from our research and experience on what good looks like. As companies scale their revenue operations. We've talked to hundreds of customers and prospects, and when we start to look at their go to market processes, they always ask us two things.

The first is, how do we compare to others? And the second is, what improvements would you recommend going forward? And so, we designed this diagno uh, the, the maturity model as a diagnostic, and the idea is to be [00:06:00] able to assess a company's current capabilities across multiple dimensions, and then provide a structure for Evaluating the current process prescribing improvements to achieve more consistent and reliable results.

And the three models that you'll see here focus on the three different disciplines on pipeline management on productivity, primarily rep productivity as it leads to pipeline development and for and and closure and then forecast maturity and the outcome we're trying to achieve. The goal we're focusing on is to help customers elevate efficiencies.

To actually take data and metrics and actually use those smartly and making decisions and then of course help with go to market and future planning. So next slide is there a stage zero with spreadsheets? Where does spreadsheets fit? And napkin? Guessing is that incorporated into this modeling somehow?

It is interesting. Um, one of the things that we talk about in this model is use of tools and, [00:07:00] um, early stage companies, of course, are heavily, heavily reliant on spreadsheet. So, uh, stage one stage zero is kind of where you'll start. But, you know, the reality for a lot of companies is. They're all on spreadsheets for what if analysis and, you know, other planning ad hoc type planning.

So it's infused throughout, but we do have a section on tooling that we'll talk about that talks about where spreadsheets start and where they end. Thank you for that. All right. We're on the same page. All right. So our focus today is on the maturity model. So, uh, in order to develop the model, we looked at data across our network of companies.

Um, and we were looking for how they compared in terms of performance and the performance that we were looking for was forecast accuracy. And so, uh, as we looked at the data, we started to look for commonalities in companies and what they were doing well and what best, best practices they were deploying.

And what we found were clear cohorts of companies and then how they progressed, um, as they scaled from [00:08:00] essentially startup to IPO and beyond. And what we found is that, uh, companies that struggle to forecast typically have very manual and inconsistent assembly, submission, review processes in place. As they scale, they have trouble tracking the types of changes, who's making those changes, when are they and why are they, is also very limited.

And then finally, these companies also had limited insight on the deals themselves, on the engagement that was happening at the deal level. And as such, they were unable to really proactively find and mitigate risks and pipeline and then ultimately in the forecast itself. And so the intention of this model is to really help companies understand where they are today in terms of their overall maturity.

Across multiple dimensions, people process metrics, tools, AI and so forth, and then more importantly, provide a path forward on where they can spend their time, where they need to focus on improvements so that they can plan that into their future go to market efforts. Um, I'm curious, Matt, based on your oversight over the RevOps co op, you know, community, [00:09:00] you, you, you know, this is the first time us presenting this framework, this maturity model to, uh, to an external audience.

In this this form, but I'm I'm curious if you've seen any similarities across your community base that reflect what you're seeing here, especially on the organizational and process maturity components. Yeah, I think a lot of a lot of the questions especially revolve around folks that are at the earlier stages, right, which kind of makes sense if you think about, you know, as folks mature means you get more sophisticated, typically have more experience under your belt.

And so a lot of the questions at least that we see pop up, especially in our slack group are, you know, related to people who are. In the, kind of the stage one, stage two, and maybe they're looking to refine their process, get better at it, uh, move out of spreadsheets, things like that, um, and kind of take things to the next level.

Uh, but that's definitely where it seems like a lot of folks are, I don't know if stuck is the right word, but maybe [00:10:00] that's the, I don't know, like the chasm, right, that they're trying to cross to get over the hard part for them to do. Uh, that's what we see a lot of at RevOps Co op. And then I know we're going to get into your specific experiences that you to me, Ben, but any perspective on maybe before a picture when you first joined.

I mean, you've gone through this massive, uh, era of scale, but when you first started, certainly wasn't as mature as it is today. So what were your experiences early on? And kind of the motivating forces behind moving up on that maturity scale,

motivating forces, partly necessity, partly responsibility. Absolutely. You know, aligned goal setting and, you know, uh, frankly, ops being there to help kind of drive the agenda a little bit. We were, we were a little bit immature and more spreadsheet oriented before we developed a proper operational model and support system.

And I think that was kind of the [00:11:00] linchpin for taking the motivation and the drive of the sales team and operationalizing that in a way that helped improve their life will also help support the growth of the business. Yeah, I think it's interesting. We just launched our trends report this morning. And one of the questions that we asked about 100 robots, practitioners and leaders was your biggest challenge going into next year.

And the most commonly cited problem that has to be addressed is process and alignment. So you had mentioned alignment is one of the key factors that kind of drove you to wanting to, I guess, move the organization forward. It's pretty intuitive, right? I'm not saying anything that's that groundbreaking to people, but it's interesting that everyone seems to always be in that mode of better alignment.

Better process, better accountability. And there's never any supplement for that. There's at some level, you have to scale up from from that starting point. All right, I'm going to comment. I would say alignment is also philosophical. You got to kind of understand where the company is and where the [00:12:00] people are and where you need to go.

You know, you could pull in a. An operations model. That's great for a company like Udemy is today. If I would try to implement what we have now, four years ago, I would have been run out the door. Yeah. It just wouldn't have worked for where we were. It wouldn't have really supported the sales motion and the sales strategy we had at the time.

And it wouldn't have been the right fit. Yeah, that makes sense. Yeah, I think we could agree, though, that consistency and standard matters, even if it's light, right? It has to, there's a foundational element that's important, and I think the data is going to show that. So, um, as we looked at the data, actually, we found some very interesting insights.

So, again, what we were focusing on was, uh, accuracy, forecast accuracy by mid quarter. And so, uh, we'll talk a bit about the differences in these companies, uh, you know, what a stage two company looks like versus stage four. But what we found is that, um, we looked across our network that, um, AE accuracy by mid quarter for stage two companies averaged around [00:13:00] 60%.

But as companies progressed, companies in different stages, if you look at stage three here, we actually saw that the accuracy improved. And a lot of this has to do with those standard, you know, Standard use and discipline around sales process, which matters as you get above three into three, four stage actually increases to 90%.

And some of our best in class customers were actually showing accuracy earlier in the quarter, actually getting closer to week six as a result. So really interesting findings in this cohort base. And we move on. Um, and then talking a bit about process has been mentioned. So process matters what we found.

So we were using, uh, we took a look at companies that had, uh, deployed and employ a sales process. So they're actually enforcing discipline around medic med pick or some, you know, standardized process. We found a 10 percent difference in Improvement and forecast accuracy as a result from those who did not moving [00:14:00] on to the next.

We also found that more frequent submission again. This gets back to process. So having a standard process, a good cadence of following, you know, essentially what is a weekly cadence. You know, Monday, you've got your one on ones Tuesday, Wednesday, Wednesday, you've got your Uh, line submissions, management submissions, you know, culminating in a Friday, uh, meeting, um, makes a difference.

So folks that are more ad hoc or who are submitting less frequently. Are seeing, you know, significant differences between those who are spending more time on that weekly cadence and building that. And for many of your companies, folks here, I know that, you know, building to a weekly cadence takes time and focus and energy to get going there.

But, you know, there are proof points that are showing that that is a difference. And then finally, one on ones actually inspecting deals, um, makes a difference as well. So again, companies that are Enforcing a standardized process where they're actually having manager rep one on ones, they're actually going and looking at engagement data, [00:15:00] they're taking a look at the AI and conversational tools that are available, looking at risk, planning strategy, has a difference, makes a difference in terms of overall forecast accuracy by A significant margin.

The 1st and 3rd are really interesting to me. I mean, I'm curious from both Matt and Ben. I mean, what do you see, Matt? I guess 1st from from the community. Um, maybe you've tapped into this. Maybe you haven't, but any perspective on like how many organizations actually don't follow a sales process. Um, a formal sales process because it's.

I guess when you're in the early stages, yeah, you're probably a little bit less mature on on all things, including on your sales process, and it's more ad hoc, but I'm, I'm curious if you have a perspective on on adherence and enforcement of sales process, then also deal inspection. I mean, this is something I hear all the time.

Um, a lot of one on ones either don't happen or they're very ineffective. In fact, reps report that a very high clip that the deal inspection calls the one on one calls they have with managers. Yeah, at any value and it seems like those that do it right. It has an [00:16:00] impact. Yeah, well, those and I think part of the reason is because those things are like easier said than done and really hard to to to actually do and to actually do well.

Right? So, you know, like, if you look at something as simple as, like, enforcing a sales process is like, Well, yeah, like, you know, that sounds great, right? Of course, like you should have a sales process and you should enforce it, right? But the devil's in the details. So a lot of the things that we see are like, well, how, right?

Like, first off, like, what is the sales process? How do you enforce it? And then how can you ensure that that actually Is enforced and enforced consistently, right? And that's where, you know, a lot of like tools, software, thing like that can come out and help. And I think, um, the deal inspection piece similar as well.

I think all of us can agree, like, yeah, obviously you should be having one on ones between, you know, sales managers and, um, AEs and, you know, you should be, you know, kind of looking at deals, poking on them, asking questions, right? But like, well, what, what [00:17:00] should you actually review? On a, like, on a weekly basis, right?

Like, what are the, what are the parts of the deal that you should inspect? What should you look at? What are the things that you should kind of poke at? And then you do that for one person. Do you do that consistently with everybody on your team? And so those things make a lot of sense to me. Um, but like I said, they're hard to do, I think, in actuality.

And they, you know, if you go back, like, If we went back a couple of slides to look at that, um, that slide that Jeff walked through of the increased accuracy as you go through the, um, as you move up the maturity curve, I think what you'll probably find is. The companies that enforce the sales process and the companies that actually do deal inspection are probably the ones that are in that box, right, that are 90 percent accurate by week six and eight because they do those things.

But those are hard things to do, and that's also why companies that are earlier on in the maturity curve may not. Be able to do them either, because they're still trying to figure those things [00:18:00] out and standardize some of those things. So they just don't have the resources and the time to do. So, yeah, Ben, I'm going to expose my ignorance here.

But is it really on ops to enforce or to mandate deal inspection at the level of manager and rep? And if so, like, how does how is that evolved at Udemy?

It's evolved at Udemy on benefit side. I would say very organically, um, you know, we haven't had a whole lot of rigor or tops down, um, process driving to the team. It's kind of been left up to regional leaders and, um, segmentation leaders on how they want to, uh, require a submission and what kind of level of deal inspection they go through.

And there's good and bad to that kind of organic evolution. And 1 is, One of the bad is the people that don't catch on quickly perform poorly. The people that do catch on are the ones that stick around and have [00:19:00] success and grow their careers and. I think just help drive the company forward more so that that deal inspection, the people that have figured that out are doing great.

People that haven't figured that out are still working on that. And hopefully they get there. Yeah, if anything else to add on this 5 year, do we want to move forward? This is 1 area, by the way, breaking down sales process, submission schedules, deal inspection specifically is going to be part of our report next month.

So look forward to that. We look at specific, um. Use cases on on who's doing it right and who's struggling with it and what good actually looks like when it comes to deal inspection The metrics you look at the cadence, um that sort of thing. So Decided to go into that in more detail now for some more practical examples that shifting from stage to stage Specifically going from stage two to stage four, which seems like the most common shift I mean, obviously there's a transition between stage three, but the biggest leap seemed to be between these two stages.

Is that accurate jeff? Well, I think that's a [00:20:00] progression. And really, as we dive in here, we're just going to compare the two different stages to give you a sense of the evolution between those two. So, um, yeah, let's, let's go ahead and compare. So, uh, organizationally, stage two companies tend to be smaller, you know, say 20 to 50 reps, definitely under 20 million.

That's not to say that companies with experienced rev op teams in stage two wouldn't have progressed further, By virtue of the experience that they have, nor does it mean that larger companies will be in stage four. They may be less far along based on what they've been able to implement. But basically what we're saying here is from the model's point of view, in order to be as accurate as we've stated in the data, there are certain foundational elements in each of these stages that need to be addressed in order to hit those.

And so as you look at at stage two and kind of go down the different dimensions, you know, this is what we call the stage of forecasting with human judgment. It's basically reps and managers providing a subjective call. Revops is tracking and providing comparative guidance based on [00:21:00] the data and the metrics that they track.

And what you'll see on average around the stage two companies is that they have a good sense of visibility and accountability and pipeline progression at the team level. So they have established a sales process. They've defined what that process looks like. They have stage gates that allow. Movement between those.

So there's, you know, at least a definition and a progression there. The company also has a solid grasp of overall conversion at the company level. So the ops team is able to take the pipeline, the funnel and be able to say, okay, based on stage, I understand when rates, I understand velocity and what that progression might look like.

And from that, that gives these companies the ability to gauge the team's accuracy and consistency within the quarter. And then compare subjective calls against historical performance. So there's at least two vectors that you're, you're, you're managing to, in order to be able to work. This is also where tools such as conversational AI, uh, provides some real value because they provide insights to the deal, uh, activity and what's going on relative risk associated, and again, are helping to highlight areas of attention.

[00:22:00] That these companies need in order to help mitigate risk in the pipeline. So shifting to stage four, stage four companies tend to be more global based. They've got multiple levels, they've got overlays, product teams, uh, and a number of folks that are reporting into that organization. Um, so much different, uh, need here.

Their goal really is to triangulate, um, across the organization. What they're looking for is ensuring accountability across the board by getting inputs across the sales hierarchy. And then looking for disagreements and opinion from those folks to identify areas of risk and further inspection. Um, in addition, the stage 4 companies absolutely, as Matt had mentioned, have a system for collaborative deal reviews.

They have a cadence for meeting and a, uh, a system of going through those inspections that again are helping identify risk. And then as they're collaborating together on submitting forecasts, the goal there is to minimize judgment errors between the lines. And [00:23:00] then in terms of tooling, for example, this is where predictive AI tools are really pivotal because They allow companies to compare the current performance with historical data and the close rates and again, identifying and surfacing risk, which is really what the organization is looking to achieve in stage for any other commentary or questions on this, Matt, Ben or or any of our participants, the attendees.

Pretty straightforward. So what we thought would be helpful is to talk to a practical example. Um, as Ben, uh, and you to me, we're 1 of the 1st customers. We, uh, I guess we presented this framework to and and worked with him on. Uh, I wanted to get Ben's take on on that transition in that journey again. Not not to tell the story of boost up necessarily, but really to tell the story of.

what it looks like to go from stage two to stage for the process and sort of that journey, the [00:24:00] difficulties sometimes accompany that. So I probably overdid it with slides here. I'm thinking alive now that maybe I went too deep, but I'm just gonna expose everything and then let you been kind of talk through it.

Whether we hit on these points or not, you know, I'll let you, you know, dictate how we go through it. But I wanted, I thought it was helpful to visualize, um, you know, this transition for a, for a specific customer. So do you want to start wherever you want to start on on how this journey began and where it's where it's landed?

Yeah, sure. Um, yeah, there, there is a lot there. Um, you know, I'll fly through some of it and happy to kind of. Sit and poke at anything that that is an interesting to anyone in the chat or on the panel for sure. But I mean, our journey is a lot like what Jeff just described, you know, about 4 years ago, we had dedicated ops and sales management doing some good calls, you know, overriding a forecasts, mostly in a spreadsheet.[00:25:00] 

We just primarily focused on quarterly forecasts. We had a routine process. I say routine, meaning it wasn't mandated. It wasn't a solid process that, you know, Monday, Wednesday, you know, Thursday, Friday kind of cadence, you know, we had clear stages and forecast categories that are pretty common. And I would say, you know, industry best practices.

Um, we understood exit criteria understood, meaning, you know, in our DNA, we kind of knew what an exit criteria consisted of, but we didn't really have system driven or, you know, rules built into our CRM driving exit criteria. So we had that solid sales process in place. Um, we had reached, I would say, a product market fit and kind of transitioned into our growth phase at that point.

So, um, I was lucky when I came in, a lot of this infrastructure was already built. And, you know, it was working pretty well for us. And in the last four years, we haven't really adjusted our [00:26:00] sales process, um, significantly, or our forecasting methodology, um, since 2020, um, we had recent data, not live data. We had some week over week variance data and some in quarter pipe create and convert data, but not as much as I would have liked, and we had zero historical or accuracy metrics.

We weren't looking at any of that. It was before I had started in 2020. It was Wild West. So I had nothing to work with when I first came in. Where we are today, we have embedded ops globally. We have four global sales VPs with a primary dedicated. Partnership to help with all things operational, including helping with forecasting.

We have an analytics team that runs a global NVP forecast projection. Um, sales management guidance on deals, amounts, and timing. Um, custom op fields, and we do run MedPick. So we've been on MedPick shop for about [00:27:00] two and a half, three years now. Um, really good CRM data hygiene, weekly cadences. Pretty good CRM architecture.

That's a journey, right? Like, that's a continual journey, is continuing to build a CRM and continuing to provide the value without overly bureaucratizing a CRM. And that's something that I struggle with, you know, weekly. And we could keep going. Um, you know, everything kind of follows along nicely with what Jeff just talked about on the previous slide.

And happy to talk through or poke holes in any of the stuff here. Yeah, we can come back to it if someone wants to look through this or ask specific questions. But the other part of this was. Okay. So of course, everyone's trying to improve the way that they do everything, including forecasting and, um, part of what we've tried to do is provide a roadmap for it.

So the purpose of this modeling is it gives you a pretty clear roadmap [00:28:00] and diagnostic, I guess, framework by which to gauge where you're at, audit where you're at and where you can go. But then ultimately, it really comes down to the impact that it has on the business. And so, um, these were things that you had mentioned, Ben.

As a result of going through this transition in a more structured way, um, what we've seen as a result there. So do you mind covering some of these? Yeah, absolutely. And, you know, this is my notes here are very missing a lot of data. And my approach to this was more, how does this make me feel than just including data?

Like we can all throw out a bunch of data points and to give people more perspective on the call, you know, four years ago. Udemy business was kind of a side hustle. That was part of a direct to consumer marketplace. Well, as I mentioned, we had found a product market fit and we were really accelerating into growth phase.

And in that time, um, you know, we've, we've earned about 15, 000 enterprise [00:29:00] customers and we're at nearly half a billion in ARR. So, um, this whole transition from phase two to phase four has really benefited. The, the DNA and the foundations of our company to be what we are and continue to target about 35 percent growth in 2024 is our plan.

So, um, continuing to grow at scale, um, and I believe we have the foundation to get there. Um, I'll just run through these points really quick because I feel like a lot of people on this call can relate to how all this, that, that sounds great, right? But that's our journey. That's not everyone else's journey.

But how does this really make you feel? What does that kind of get you day to day, especially as we're, you know, in December looking down, you know, the barrel of the end of the year, um, one, this is obvious improved sales execution. Um, you know, we're so much better at identifying and swarming the right deals earlier and [00:30:00] understanding risk and taking more decisive action or not taking action, right?

Sometimes not taking action is just as valuable. Hey, this deal is not going to come in right now. There's three other deals that I need to go focus on. And I think we have, we're in the spot where we can recognize that earlier and arm our team with where they should be spending their time. Efficient resource allocation.

Again, the obvious is, you know, standard marketing needs, customer success, resourcing CFO level decision making, but less obvious areas. But 1 example is I used to get hit up by our head of deal desk and finance team asking for my perspective on, hey, what is the last week of the quarter look like? What deals are going to come in?

Um, and I think everyone, a lot of people in this call have probably been in that situation. Um, I don't get those calls anymore. We have visibility and we have an understanding of how this works and what the end of the quarter is probably going to look like based on the information that we have. Um, executive [00:31:00] expectations.

Aaron, you were kind of talking about this earlier, um, CEO breathing down your neck about certain things and completely ruining your day or your week. A lot of us on this call have probably been in that role or are in that role where we've been inundated with executive update requests the last week of the quarter.

And our execs now have a lot more confidence in what's happening and they don't cause as much scurrying as they used to. And I would say we're now pretty consistently within that 90 percent accuracy range. At week 6 to 8, maybe probably creeping up from 90 percent more like 93 or 94 percent here in the next year, um, and then scalability, uh, every stage 1 or 2 company.

I've worked intended to overestimate themselves when entering new markets, releasing new products or making acquisitions and where we are. Now we have the framework and modeling to more quickly. I would say, evaluate and execute and iterate. [00:32:00] On scaling the business, so an ops that helps us see around corners and really provide strategic consulting to the business and not so much reactive question answering and looking at this framework for me and my experience here at Udemy, um, this feels really good compared to where I was 4 years ago.

Yeah, and I love the emphasis on the fact that this is. This is impacting the broader business. It's not just about having, you know, a forecast number that you can call and have confidence in it affects everything else that you're doing. Um, and for an operation team who. May or may not have, you know, a foothold in the at sea level may not have the influence that they want.

I mean, think about amplifying the effect that you have on the broader business by tackling these, these, these initiatives that are getting in the way of proper planning and proper execution across revenue. And that's, that's what's really exciting. So the marketing narrative here [00:33:00] is, uh, uh, what did we say from spreadsheet IPO?

That's, that's really what we're trying to accommodate here. The Udemy story is a good, a good example of that. Um, I'm reading a question here from Amanda. How do you migrate forecasting risk due to sandbagging in happy years? Uh, using the example of deals, uh, being held back and, uh, non committed stages and, and hope casting.

Any perspective there from, from either of you?

That's a tough one because you're getting into culture here and different personality types. Um, You know, my comment here, illumination equals or less rumination. Um, I feel like in my experience, um, before and during my time at Udemy, transparency and partnership and bringing to light information to the right people helps them understand the problems they need to solve.

[00:34:00] Um, again, that's the right people. So if you have an issue with a VP or a team and you feel like, you know, some of these behaviors are pretty common, uh, data and partnership and conversation and usually, in my experience, helps, helps that sometimes getting the data is the hard part. And, um, that'd be something I'd be happy to chat with you about, you know, offline if, if anyone wanted to connect with me on how we've done that here.

You know, I've heard, I've heard reps will be reps, but I think your point about this being a cultural phenomenon is really true. I mean, as a former enterprise seller, I can tell you that yes, reps try to get away with what they can get away with, but if you're on a group pipeline call with your CEO grills you with five or six questions about every deal that you are either confident in or not confident in, you know, After a couple of those types of calls being humiliated in front of a group, it kind of washes out the bad behaviors pretty quickly if they ask the right questions and are focused on the right metrics.

So [00:35:00] I think being focused on the right KPIs is critical as you're going through deal reviews and certainly having good pipeline calls can benefit the whole team to scrap out all of the nonsense behaviors that become becomes pretty common amongst AEs. Matt, anything to add there? Anything that you see from the community that might get in the way of these cultural components?

No, I was just gonna, uh, kind of, uh, you know, put the thumbs up emoji on what Ben said around data, uh, you know, again, like, that's just the, the, it's the clearest way to bring, um, like, just overall transparency to the discussion and kind of something that people can't necessarily, Argue with and try to strip the emotion out.

Uh, the hard part, like Ben said, is making sure that you're able to, to get your hands on the data you need to, to bring to, to the table. Um, but yeah, focusing on what the numbers tell you, uh, and really centering your discussions around that are good ways to get rid of those. Happy [00:36:00] years and, and sandbagging in addition to all the stuff you mentioned to Aaron, right?

No one wants to get humiliated multiple times on a forecasting call. And yeah, those things will definitely, um, take care of themselves. And that happens more than once too. That's a core brand philosophy of ours, by the way. I mean, access to the right date at the right time is what opens up visibility, which is what allows for alignment, which is what allows for accountability, which is what gives teams control over outcomes ultimately.

Let's them hit what they need to hit on number four scalability at an efficient pace. Um, cause I, you know, I love that you focus on that. A lot of people think about skills, think of scale as adding bodies to a problem or money to a problem. And it's not so I doing better with either what you have or maybe even less or getting more from the resources at that are available to you.

And I think a lot of people miss that point. Um, all right. Uh, Jeff, back to you on this point. Yeah. Aaron, how do we want to handle timing? Let's, uh, give it another. Five minutes, and then we'll [00:37:00] wrap up. Maybe we cover this slide. We quickly go through the next one. I can maybe hurry up through this. Yeah, we can build it out.

So I think what you're hearing from the conversation today is that there are no shortcuts. and building out this capability. Um, there are foundational elements that are needed, um, and, uh, need to be built out as, as part of your organizational growth. So it starts with sales process adherence. So we've been talking quite a bit about that.

Um, you know, basically a way of, of inspecting deal progression, monitoring data hygiene, and just a note on that. I know how hard that is for everybody. It's a constant challenge, but It's going to become more important than ever as you start to apply AI and predictive tools. AI can get around some of it, but you know, the more accurate the data, the more precise the model is going to be.

And then that, that discipline that you have in the sales process flows right into the forecast process. It's a continuation of the same disciplines, a consistent cadence, and then, uh, inspection early quarter on identifying what's healthy and not and progressing that forward. And then late in quarter on managing risk.[00:38:00] 

The inspection and coaching is really about identifying risk, putting together deal strategies, ensuring accountability across the teams. And then the mathematical analysis is really, you know, taking and triangulating data across multiple sources and data points, getting that subjective and objective input, and then creating as many vectors as you can to give you a range so that Your CRO and your sales leadership can apply their judgment and experience on what's happening internally and what may be happening externally to, you know, come up with a number that they're confident with going forward.

And then Drew had mentioned, you know, when, when you get off spreadsheets, um, the, uh, this is just a handle on the kind of tools that are really needed to. Enforce process. Matt, I think you talked a bit about this. You know, tools can help. You have to define it. Tools can help enforce it. Um, and so thinking about, you know, how do you enforce sales process?

Well, your CRM CPQ contracting ideas to standardize and [00:39:00] speed the process you've got. Consistency of engagement with your inbound and outbound pipe gen tools on the go to market side. You've got pipeline and sales management and obviously that will manage that process, but it also will provide data on actual performance so that you can use in the go forward capacity and territory planning, which is essential for next year.

On the sales coaching, you've got your call intelligence, your sales enablement tools. And then, uh, clearly for mathematical analysis, you have your data warehouse to be able to take all this data from these systems, uh, determine the historical performance, figure out what the win rates and the ratios are, and then, um, start to correlate, you know, analysis on effectively what's winning behavior.

What does it take to give deal across the line is most important. And so you'll see the full set of tools here. The reality is, um, you know, most companies in earlier stages will do a lot of this in spreadsheets. Um, and that's okay. Um, it's, you know, key key thing to get started and then [00:40:00] build from

very good. And we had mentioned this at the beginning. Um, more, um, more to come on the maturity model front will release going into next year. But we wanted to let you know ahead of time that we've got a lot more in the works. And again, the report that we're going to be sharing on forecast maturity includes everything we shared today, plus a lot more data and a lot more detail with some actionable Steps on best practices and where to start.

So look out for that. We'll send that to everyone. I uh shared in the chat The trends report that I mentioned we launched it today But to avoid having to go through another form or registration, I just posted the link so you can download it directly I take advantage of that real quick. Um, and, uh, I'm going to open this up for, uh, for questions, but I also wanted to make sure, uh, um, I, I plugged this real quick.

So, you know, we, we talked a little bit about, uh, process alignment, visibility. I made the point about visibility leading [00:41:00] to alignment, accountability, and control. I'm seeing that, um, a lot of people are struggling to, uh, To just see what they need to see so they can start taking action on some of these critical components, these critical initiatives.

We, uh, we wanted to offer our platform for free, um, on a trial basis for 60 days so that you can at least get a really detailed summary of, of, of different data points, different, um, um, funnel analytics, uh, a view of productivity pipeline and forecasting process and metrics that. Are probably going to be critical for you to close out Q4.

I guess you can call this an early Christmas gift, but we wanted to expose this to everyone. If you want to take a quick snapshot of this link. Actually, let me let me see if I can't copy it in. Um, if you want to a free trial. Boost up there you go this 1, you'll have to go through a form so we can process it appropriately.

So sorry about that. But at least you get. Free trial of the platform, a lot of really cool dashboards and reports that will hopefully help you close out Q4. [00:42:00] And then that trends report, which is, you know, 100 plus rev ops leaders and practitioners that weighed in on trends for next year and the things that they're worried about and thinking about, which I think was really beneficial for us as a team.

I've gone a little bit over time, but we can stay on for, you know, 2, 3 more minutes. If anyone has any last minute questions that they want to ask. And if not, maybe parting thoughts, if any, from the panel. I know the one thing I was thinking about as you were, uh, kind of closing things out, Aaron, of, you know, looking at a maturity curve is, I think, one understanding that everyone starts at stage one, right?

I don't think anyone, anyone leapfrogs automatically, like, regardless of how incredible and great you are, to, like, somehow magically starting at Q4. And I think. You know, you probably have to go through all these stages in order to, um, like get to stage four and stage five as, as well. I, I think it would be probably really hard to leapfrog anything.

Yeah. [00:43:00] Um, so yes, I think that's kind of the key point of all this is, you know, hopefully one this helps you understand gauge like. Where am I today? And what are the things that I can do to move up from where I am today to the next stage? And, you know, I think we talked about why it was important up front, right?

Like go from 60 to 80 to 90 percent forecast accuracy as you move up the maturity model. That's why you want to do it. Um, but yeah, just understand that, you know, unfortunately probably no, no shortcuts, no leapfrogs that can be made along the way. Yeah, it's a really good point. I'm going to show my whole whole screen here at the risk of maybe sharing something I shouldn't.

But, um, there was a more detailed version of what we went through with you to me. And this is something that we're offering everyone on some level is a very thorough analysis and audit of. Organizational process maturity tools, a breakdown of reporting, a kind of scoring of where you're at at different junctures, um, and each of these metrics, again, this is [00:44:00] built out as a diagnostic tool, but we're now using it to help customers and prospects move through their, their evolution of forecasting behaviors.

And so. This is the kind of thing that we would do with you on a more, much more granular level. If anyone is interested, we can certainly engage with you on that. All right, well, I appreciate the audience participation, the panelists. Thank you so much for giving us your time and everyone else. I appreciate you, uh, signing in.

Have a great day.

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