212. George Storm, CRO at N.rich - Why your SaaS Forecasting Is Broken & Inaccurate

Summary

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The SaaSiest Podcast – Episode 212

Guest: George Storm, CRO at N.rich
Topic: Why Your SaaS Forecasting Is Broken & Inaccurate
Release Date: May 28, 2026
Hosts: Daniel Nackovski & Thomas Sjöberg

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Episode Overview

In this episode, Daniel and Thomas sit down with George Storm, Chief Revenue Officer at N.rich, to dig deep into the fraught world of B2B SaaS forecasting. George candidly shares why conventional forecasting models no longer work in today’s fast-changing SaaS landscape and lays out a new, more dynamic, and market-aware approach. The episode is packed with actionable insights for CROs, VPs of Sales, and RevOps professionals—plus candid stories, a healthy bit of skepticism around current best practices, and some refreshingly direct advice.

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Key Discussion Points

1. Meet George Storm & N.rich (03:36–09:13)

• George’s background: Over 20 years in sales, 12+ in B2B SaaS, ex-Scribe, now CRO at N.rich (a Finnish ABM platform based in Stockholm).
• N.rich Quick Facts:
  • ~65-70 employees, fast growth mode.
  • ARR: €6 million (16:01)
  • Customer base split almost evenly between North America and Europe, ~75 customers.
• Favorite business books:
  • Hope Is Not a Strategy by Rick Page—fundamental for enterprise sales. (06:02)
  • Eat That Frog —a compact read on prioritization and time management. (06:53)
• Defining ABM: Account-Based Marketing is essential for breaking into crowded markets with long buying committees; it’s more than just a CRM checkbox. (09:20)

“It doesn’t matter how good multithreading you do if the entire thread gets cut on the buyer side. What you did is completely immaterial.”
– George Storm [00:30 & 25:10]

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2. The State of Forecasting in SaaS (17:47–20:13)

• Forecast misses now come as a surprise for both companies and investors—often indicating a modeling problem rather than poor execution.
• The core issue: SaaS leaders are still using outdated, rigid forecasting models in a volatile, rapidly changing environment.

“The problem that I have with my CROs is not only that they might have a bad quarter… it’s that this miss comes as a surprise both to us and, transparently, for most accounts, to them too. Which is, in my opinion, a modeling problem.”
– George Storm [20:13]

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3. Why Traditional Forecasting is Broken – The Three Pillars (20:13–26:56)

a) Over-Reliance on Absolute Numbers

• Forecasts present a single “target number,” but in reality, outcomes should be modeled as ranges or curves, reflecting probability, not certainty.
• Rigid numbers don’t account for changing conditions.

b) Outdated Cadence

• Most companies set annual forecasts, then stick to quarterly reviews—lagging far behind actual market dynamics.
• The December forecast is already obsolete within weeks.

c) Ignoring External ("Macro") Factors

• Most forecasting remains “inside-out”— focusing only on internal metrics (pipeline, win rates, hire pace), ignoring external shocks: layoffs, M&A, competitor actions, interest rates, etc.
• These external events now have outsized impact and are impossible to influence from the seller’s side.

“Forecasting is broken today because our environment and our circumstances have changed… there are macro signals out in the market that we can do, pragmatically, absolutely nothing about.”
– George Storm [23:54]

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4. Breaking Down Old Forecasting Models (27:44–33:48)

• Traditional “stage-weighted” pipeline models give a false sense of control and accuracy.
• Personal (“gut feel”) confidence ratings and past win rates are unreliable—historic data doesn’t apply in today’s turbulent markets.
• Legacy models don’t account for how AI and market disruptions rapidly shift buyer behavior, needs, and risk tolerance.

“You can’t trust historical data. In today’s market, it’s almost mathematically impossible because the speed of the market…”
– George Storm [31:53]

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5. The Modern Forecasting Approach – The “Forecast Loop” (37:19–44:48)

The Forecast Loop Steps

1. Aggregate Data
   Pull both internal and external data points regularly.
2. Interpret & Analyze
   Use probabilistic models (like Monte Carlo simulations) instead of static numbers.
3. Decide & Act
   Make decisions based on live signals—e.g., increasing top-of-funnel if win rates drop.
4. Iterate Rapidly
   Move from quarterly to weekly (or even faster) reviews and adjustments.
5. Monitor Macro “Regimes”
   Classify markets into three weather regimes:
   • Calm (stable, predictable)
   • Turbulent (delayed, risk-averse)
   • Stormy (marketwide disruption)

“I use three regimes… Calm, Turbulent, and Stormy weather… Regime change is a core forecast driver.”
– George Storm [37:19–41:12]

• Use real-life signals—customer calls, conversation intelligence, news—to trigger regime changes, not just your own spreadsheets.
• Be ready to adapt plan parameters: expect compressed ACV, longer cycles, and higher churn in turbulent/stormy times.

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6. Practical Monitoring & Adjustments (44:48–47:41)

• Track keywords and themes (“budget freezes,” “team layoffs,” “merger,” etc.) across all sales and customer conversations.
• If macro factors start hitting your accounts, downgrade your regime and adjust forecasts accordingly.
• Encourage a culture where adapting early to regime shifts is rewarded—late reactions lead to “surprise” misses.

“If you do this quarterly, it’s going to be too late. By the time you realize you’re in stormy weather, your win rate has dropped… you’ve lost the quarter and the next is already at risk.”
– George Storm [47:09]

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7. Implications & Organizational Impact (48:59–51:52)

• Turbulent times are also rich with opportunity for agile SaaS companies.
• N.rich is building out product and organization for extreme responsiveness—mirroring AI-native companies’ pace.
• The forecast loop approach isn’t just about revenue—it’s an operational philosophy for product, marketing, and hiring as well.

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Notable Quotes & Moments

• “Forecasting is not just lying down and accepting ‘Okay, my win rate will fall; I might as well like submit my resignation to my board.’ But how… can I counteract this now?”
  – George Storm [47:13]

• (On what he’d wish for in the organization)
  “I always need salespeople. My least favorite part of this gig… is hiring salespeople. It’s very unpredictable and super, super volatile.”
  – George Storm [51:14]

• “Ownership of the number doesn’t mean you can ignore the weather.”
  – Paraphrased from multiple comments [41:55]

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Actionable Takeaways

• Stop forecasting as a static, inside-out quarterly exercise.
• Adopt “regime-aware” forecasting: continually rate the market environment and update forecasts accordingly.
• Make probabilistic, range-based predictions (Monte Carlo simulations, scenario ranges—not single numbers).
• Monitor both internal and external signals; adapt quickly if layoff waves, mergers, AI disruption, or other macro shifts appear.
• Increase the cadence of reviews (weekly, even daily if practical).
• Train your teams to think in terms of dynamic loops, not static plans.

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Recommendations from George

• “Best business book to this day: Hope Is Not a Strategy by Rick Page.” [06:02]
• Inspirational external guests: Jako from Winning By Design (52:03) for more on sales/forecast modeling.

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Key Timestamps

| Timestamp | Segment | |-----------|---------| | 03:36 | George’s intro & background | | 06:02 | Best business books | | 08:01 | What is N.rich & their ABM focus | | 16:01 | Business snapshot: ARR, growth | | 20:13 | Why forecasting is broken | | 23:54 | Pillars of change (math, cadence, macro) | | 31:53 | Why historical data is unreliable | | 37:19 | New forecasting approach—forecast loop | | 41:12 | Market “regimes” & external signals | | 44:48 | Monitoring and regime adjustment | | 47:41 | Making operational decisions | | 51:14 | What George is hiring for | | 52:03 | Podcast guest recommendations |

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Episode Tone & Style

George is direct, analytical, and pragmatic. The hosts keep the tone conversational and informal, encouraging storytelling and concrete how-tos, making the episode practical, accessible, and hands-on.

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For Further Discussion

• Connect with George Storm on LinkedIn for deeper dives, data, or challenges.
• Check out the referenced article on dynamic forecasting (noted by the hosts).
• Consider joining the SaaSiest Executive or CEO networks for more peer conversations.

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Closing Thought

“Having this perspective where we don’t just look from an inside-out perspective, we should have an element to bring in an outside perspective—find a way where our forecast becomes much more accurate.”
– Daniel Nackovski [56:14]

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Transcript

[George Storm]

You are listening to the Sassiest podcast in the world.

[Thomas]

Born in the Nordics.

[George Storm]

Democratizing B2B SaaS knowledge everywhere.

[Daniel]

Hi, I'm Daniel.

[Thomas]

And I'm Thomas. And we are experienced SaaS professionals that are curious about how other successful SaaS companies go to market scale, build winning teams and great products.

[Daniel]

Join us on our journey as we speak to SaaS leaders trying to get hold of their secret sauce.

[Thomas]

And today's guest is George Storm, the CRO at Enrich.

[George Storm]

It doesn't matter how good multithreading you do if the entire thread gets cut on the buyer side. What you did is completely material.

[Thomas]

Hello and welcome back to the Cessist podcast. Glad to have you here. We are in intense times. We came out of Cecius 2026 in Malma, our 5th year anniversary, and we are not on the lazy side. We will soon, in just three weeks be down in Paris and Munich for our maiden events.

[George Storm]

And.

[Thomas]

And it's a lot of fun, Daniel.

[Daniel]

It's a lot of fun. And first of all, I want to say, if you were with us in Malmo, thank you so much. Yeah, we've done this five years now in Malmo and I personally felt like. And of course it's like, how do you measure something like this? But I personally felt that the community feeling was the strongest we've ever had. It felt like, you know, I don't know, maybe it's the world out there, like it's changing fast and so on, but all of us, we needed each other more than ever. And I could feel that in that room. It was, it was really special. And thank you everybody for making it also for me and Thomas, a remarkable experience. And now, like you said, Thomas, we're quickly moving over to our opening act. So we're hoping we can bring some good people together in Munich and in Paris. So June 16, we are in Paris. June 18, we are in Munich. So if you are there and if you want to meet some great German and French, French SAS leaders and AI leaders, we'd love to see you there. And it's very easy to read up on this. So sasiusparis.com or sassismunich.com that's where you find all the details.

[Thomas]

Yeah. And if you have any other questions around it, you can just reach out directly to me or Daniel and we'll tell you more about it. Today we are going to focus on something that is on Every CROs or VP of Sales mind at least a couple of times a year, maybe it should be often. And that is Forecasting. Daniel, have you done a lot of forecasting life?

[Daniel]

I have done a lot of forecasting in my life and I lived in worlds where we would forecast quarterly and six months at a time and one year at a time. But we would also like follow this up and adjust and change at least on a weekly basis. And there's not always changes you do on a weekly basis, but it's a topic that is close to my heart. You live and you die as a CRO or VP sales with your forecast. So I'm keen to see where George take us today because he has a firm opinion that the way I used to do forecasting when I had a real job and I think the way most people do forecasting is not necessarily the way forward in the future. And he has developed this new method that he's going to walk us through here today. So I'm excited. I'm certainly going to learn a lot.

[Thomas]

Yeah, he's not shooting from the hip.

[Daniel]

No.

[Thomas]

So he has a lot of input here that we think would be very valuable for you. So let's go and talk to George. Today. We are super excited to have George Storm here as a guest in the Sassiest podcast. So welcome George and good morning.

[George Storm]

Good morning. And super, super excited to be here with you guys.

[Daniel]

So I know just before we hit the record button here, you were saying like you just came back from three weeks long travel. So where have you been, what have you done and where are you right now?

[George Storm]

I am in Stockholm right now. Where have I been? That's a good question. So the last three that I remember in order, I will try so Amsterdam, London and the last but definitely not least was Malma for Sussex for this year.

[Daniel]

Lots of traveling in your gig, in your role. Like I can appreciate that. I remember when I had a similar role. Like it's you got to be out there, you got to be out there on the field. Like business doesn't happen by itself. We're going to talk about business in just a few moments here.

[George Storm]

Yep.

[Daniel]

Tell us for the ones that don't know George Storm, who are you?

[George Storm]

Who am I? So I have been will start from the, from the business side and sort of spill over into a bit more personal, I guess. So I've been in sales for what is it? Plus 20 years. 22, 23. Time passes very fast apparently. I've been in B2B SaaS for the last 12, 13. I spend almost 8 years in a Swedish company startup scale up now called Scribe doing E signing and electronic IDs and now my role is a CRO at Enrich, as I said, based in Stockholm, married, two kids, two cats and originally I am from Athens, Greece. I lived in Stockholm, I had the pass in London and the last few years I ended up back in Stockholm.

[Daniel]

Okay, I can see in the back. So if you're only listening to this right now, you don't see what Thomas and I see, but you have an impressive bookshelf. Like somebody over there is reading a lot of books. Like what's your go to book there? What's the best book in that shelf?

[George Storm]

The B depends on it depends on which category you want because there is a lot of fiction and non fiction behind me and these are not all the books by the way. There are more bookshelves because we all four people in this household thankfully read the best business book to this day that I've read. It's pretty old, but most of the lessons still very much apply is Hope is Not a Strategy by Rick Page. I love the motto, the tagline. I love the book. And since I spend most of my years doing enterprise sales specifically and it is primarily an enterprise complex sales guide, I absolutely love it.

[Daniel]

Okay.

[George Storm]

If I can add a second one, I would be Eat that Frog which is about prioritization and time management. Also highly recommended. Very, very thin and short book.

[Daniel]

Never heard of that one. Thomas, did you hear. Have you heard about Eat that Frog before?

[Thomas]

Haven't heard about it, haven't eaten it.

[George Storm]

I haven't eaten the frog. That is nobody. It's actually it is something that

[Daniel]

and

[George Storm]

all the CRO Nicholas at Scribe gave us as when we were still account executives back in 2016 that was about prioritization and time management. It is a very short book, appropriately if you are in a time crunch around I don't know, half an hour, maybe an hour to read. But I still apply a lot of it. Good today.

[Thomas]

Maybe we should also circle it in our small organization. But okay. You mentioned that you now work as a CRO at Enrich. So can you tell us a little bit about the company, what you do?

[George Storm]

Of course. So Enrich is a Finnish company. We're around 65, 70 people. And I'm saying around because we're recruiting quite quite a bit lately. What we do, we are, we are an end to end ABM platform. To quote Daniel now. And I will keep doing that for a while longer. The number one European based ABM platform, which is something that I'm quite proud of.

[Thomas]

Right.

[George Storm]

And just to since ABM is a quite Convoluted term usually account based marketing, the way that we see it is essentially marketing for companies that address either enterprise or high Soviet sales or high ticket item sales sales led organizations that have to influence several stakeholders within an account.

[Thomas]

Why do you need an ABM platform? Isn't it enough just to have a checkbox in your CRM that says that this is a prioritized account?

[George Storm]

That would be awesome if you could do that. So you do need an ABM motion and by actually the platform is a derivative. The motion is what matters. Matters primarily because ABM is required because the market is very, very crowded. The stakeholder count has increased a lot and the way people select solutions now, I mean if we're talking software specifically, the vendors are selected are usually the two, three that are shortlisted. When people first start looking at something, if you're not in that list, it's very likely that you're gonna get the business. I remember it, I think it's. I don't know if it's a coin term but I remember funnel calling this the day one battle, especially for enterprise deals. If you're not in the early consideration which you can achieve by running awareness campaigns, running, trying to impact the brand presence that you have in segments and Personas in different markets, then it's going to be very, very hard for you to be there.

[Thomas]

And who's your ideal customer and who's the user? Is it predominantly the marketeer or is it the salespeople or both here. And yeah, what kind of companies work in this?

[George Storm]

Starting with the Personas. I would say that the buyers have been historically the marketing trifecta. So CMO VP marketing head of DemandGen now actually it has started to shift since actually mid last year I would say where my peers CROs are involved in these discussions, we are realizing that pipe is drying out and we need to do something else other than social selling and LinkedIn and checklists as Thomas said. And also an emerging role that I see a lot is revops or marketing ops sitting on the entire stack for revenue.

[Thomas]

So is it a lot mapping out stakeholders and keeping track of all your awareness creating activities or. So I've never been in an ABM platform. If I'm going to be no totally honest.

[Daniel]

Asking for a friend, Asking for a

[George Storm]

friend, asking for a friend. Okay, to your friend. Then the point is the following. So we're looking essentially at account progression. Let's say pick a company Thomas that you want to work with to give you an example now.

[Thomas]

All right, so let's say that I want to work with 11 labs.

[George Storm]

11 labs. Okay, so let's say that you want to work with ElevenLabs and they have no idea who you are are true and true. If. If anyone is listening, contact him. So if you want to talk to 11 labs and they have no idea who you are or what sassiest is there, what you want to work is, instead of having a BDR call him out cold and say, hi, Thomas from sasius really wants to talk to you. The likelihood of that converting is, to be honest, according to statistics, usually around.07%, which means that in order to influence that company, you need to work with what we call account progression. So the 11 labs now needs to move from having absolutely no idea who you are or what it is, what your category even is if it's not very common, to having seen the brand a few times, having seen your USB a few times, and your value proposition, maybe having seen you or the podcast or the events a few times. And then. And we track this is part of what. The first part that Enreach does is put your brand and put your name and your value proposition in front of the entire stakeholder committee in different ways of elevenlabs with ads, depending where they. Depending where they are, and then track the signals down the funnel. Are they engaging with your content? And then once the first party signals, once they start interacting with your ads, video and text and various others up from a threshold and a, then that account will be flagged as engaged or hot as we call them. At which point it makes a lot more sense for you or your BDR team to reach out.

[Thomas]

Okay.

[George Storm]

Or if the conversion points are really, really strong on the website, once you bring them there to convert directly.

[Thomas]

Interesting.

[George Storm]

So that's the, that's the idea.

[Daniel]

All right. I can see in tama sized and

[George Storm]

I have to, I have to say. Sorry to interrupt, but I have to say that there is this huge amount of complexity perceived in abm. And I understand that it is. Pragmatically, it's. It's more complex process than I described. But essentially for. For my peers, we can see it exactly as pipeline progression. It's top of funnel activity for marketing and for awareness. So we're essentially warming up and informing our stakeholders in committees in that sense, what we do to increase our conversions later down the funnel.

[Thomas]

When you describe it, I want it

[Daniel]

11 labs. Here we go.

[George Storm]

11 labs.

[Daniel]

Yeah.

[George Storm]

Yes.

[Daniel]

All right. So George, let's put some quick numbers on the business so people know what type of business or organization you're Representing like what can you tell us about what's your current ARR? How fast are you growing? You did touch upon a little bit about how many you guys are. But tell us also like how many customers do you have? Where are the customers based? Is it here in Europe? Is it the us? Whatever you can give us, we'll take it.

[George Storm]

Perfect. Okay, I will start with the last question. Where the customers are. And I can actually give you almost, almost a split of where our revenue comes from. And I was running these numbers actually yesterday night.

[Daniel]

Mm.

[George Storm]

And North America and Europe are head to head right now. It's almost, almost equal. And Europe is Nordics and Western Europe. Nordic Western Europe and UK and North America. We have primarily the us.

[Daniel]

Gotcha.

[George Storm]

There are. And it depends how we announce and how we talk about these things. Right. Because we have customers in APAC as well. I don't know if it is having a few customers in APAC. You say that we are in 192 countries, but yeah, the main two clusters is Nordics, Western Europe, UK or Europe and then North America customers we have. It is upwards of 75. I have to say we have the tightest ICP that they have ever worked with. So quite restricted lists that we're working from. And when it comes to the RR we are currently at 6 million euro. That is. What else did you ask me? CAGR or growth rate. So from last year we are currently pacing at 30%.

[Daniel]

Nice, nice, nice, nice. And I mean we know you're CEO a little bit. We know that the financial journey you guys have been on and we know that you're also on a very nice trajectory here. Now what we wanted to chit chat with you about is that you've been quite vocal about forecasting in B2B SaaS and essentially saying the way we've all used to do it, it's broken, it doesn't work anymore. And that you potentially have identified a new method. At least it works for you. And something that you'd like to tell us about here. But tell us first what you mean. What's broken with forecasting today, in your opinion?

[George Storm]

Yes. And I will have to also give you a bit of credit in sort of this idea forming. I had a lot of discussions in Malmo in the executive dinner. I particip and talking to a lot of my peers about forecasting.

[Thomas]

Okay, so that's what you did. Yeah, that was good, good topic at the dinner. Topic.

[George Storm]

Yeah, it was, it was. It was a really good dinner topic actually. I think that as Daniel said I am quite vocal and I am very, I would say math nerdy or number obsessed as I've been. I've been called a few times and we were talking about forecasting. I'm looking at my own forecasting coming back and I was like, okay, this fundamentally doesn't make sense how we do it. So to answer your question, Daniel, of why it doesn't work and why so many people have been actually not now, but like even post Covid, we have been consistently off in a lot of places is that there are three main things that have changed and I will try to sort of frame it in three pillars and then we can expand.

[Daniel]

So George, we wanted to talk to you about forecasting. You've been quite vocal about the way that traditionally we've been forecasting outcomes and revenue in B2B SaaS companies that essentially you think it's broken. You don't think it's broken. Your firm opinion is that it's broken and that there's a better way of doing it. Tell us, what do you mean by this?

[George Storm]

Yes, and I just wanted to give credit to you guys partially of how this whole thing started and got together, actually me being a lot more vocal about this topic because forecasting was a big topic of conversation when we were sitting at the executive dinner in Malma. Actually I was talking to and unfortunately I don't remember who that was that I was having this conversation with. Otherwise I would love to give a shout out here too talking about CRO tenure currently because my peers are like long 10 years have becoming a rarity in SaaS apparently for CROs. Lately it seems that the seat has become a lot more volatile, a lot more dangerous. And I remember having these discussions with the VCs and private equity operators talking about primarily forecasting and saying that the problem that I have with my CROs is not only that they might have a bad quarter, that they miss a quarter, is that this miss comes as a surprise both to us and transparently for most accounts to them too. Which is in my opinion it's a modeling problem. It's not that people are. My friends at revenue don't pay attention. I think it's primarily a modeling problem. And what I mean by that is I think that forecasting is broken today because our environment and our circumstances have changed and the change have happened in three main levels. And I will explain the three levels and then we can go into depth in each. The first level, and it's always one of my favorite topics is the math in itself. We have been used to reporting KPIs or outcomes or the forecasting number as an absolute number. But it's like if you look at it practically, it's not all of these numbers, anything from NRR budget, acquisition, forecast, win rate, all of these numbers are essentially a range. You need to calculate them on a curve based on conditions and that then inform probability. So essentially you would pick your win rates out of a curve because dealing with absolute numbers makes the model very rigid, quite inflexible. Then the other thing that is very, very problematic in today's market is the cadence in which we do forecasting. We usually do forecasting quarterly. We update the board. I mean, depending on how your board works, you maybe you update monthly, you update pace. But like your main forecast sits, we do it first time in December for the next year, and then we

[Daniel]

say

[George Storm]

that we do quarterly. But in most scenarios we're trying to catch up on what we promised in what we promised in December. I already see. And the ones that are watching that are listening to this in commute don't. But I see Thomas smiling with me saying that. And I think that it is in the way that the market behaves, trying to catch up. A number that we locked in in December is quite unrealistic given the pace that things change. So essentially we are setting ourselves up to fail. We're baking in, we're locking in a number. Circumstances change, we make operational changes, and then we still report in a cadence that sort of lags behind what's happening. And the third and the most important and the most time relevant is that we are doing forecasting very much inside out, looking into either primarily or in most scenarios, to my experience, solely internal signals that affect forecasting. We look at micro conditions. If I am, to use a bit of statistics or economic terms, we're looking at our own sales team performance, our win rate, our acv. And these are things that are weak in effect within the company. We are always talking about hiring, hiring pace, acv, win rates, regional focus, things we can touch and affect us CROs or sales directors or whoever you might be. The problem with that is that there are escalating circumstances. So macro signals out in the market that we can do well, pragmatically, absolutely nothing about. So we're talking about interest rates, we're talking about staff turnover. So as I was saying, my friends in the same seat, CROs, CMOs, see whatever, are getting fired to the left and right. Teams anywhere from BDRs to RevOps to marketing are getting either cut in half or Cut altogether or reduced. Which means that to give a very tangible example, it doesn't matter how good multi threading you do if the entire thread gets cut on the buyer side, what you did is completely material.

[Thomas]

Yeah. So it seems that, I mean, there is quite a lot of work for the CRO, the person that are doing the forecast here in order to get sort of more realistic one. And you started mentioned that instead of working with fixed numbers, a lot of things are actually curves or sort of. And how do you work with that in practice? I mean, it's much easier to work with a fixed number. Right. So how do you put that into your forecast without people saying that, you know, well, it becomes not maybe clear enough or that you are not putting your confidence in sort of one number.

[Daniel]

Because I see your point, Thomas, because I was thinking about that when we, George, we come from the world where a salesperson would take their pipe through certain elements or certain stages, call them whatever you want. And we would know based on historic data, stage one hit rate is 20%, stage two is 35% and whatnot. And then you do some weighted math that gives you a number that you can do whatever you want with. Maybe it's super accurate, maybe it's not.

[Thomas]

And it's easy to defend it. Right. Because you have the historical data and all of that.

[George Storm]

Yeah.

[Daniel]

And it was easy for the CFO to track and so on. And then the other element we added to that, we added, call it a personal confidence level, which we labeled in three segments, like, okay, what is the worst case scenario for you in your pipe, regardless of where they are in what stages this quarter. And then salespeople would have to commit. Like even if the sun doesn't go up tomorrow, my worst case scenario is I bring in 100k. Yeah. Okay. And then they had to list, okay, which deals are making up for that 100k. And then we did the same thing for realistic. What is realistic? Like the worst case. Plus some things, they're not there yet, but you know, in two months they will be there yet. And then the best case for us was essentially anything you have listed in your, in this case, Q2 quarter, if all of it comes in, that is the best magical case.

[George Storm]

Yeah.

[Daniel]

And then what we used to take in our world, we used to work with a realistic number.

[Thomas]

Yeah.

[Daniel]

And that most of the times would make sense. But I can see how that works when you have, I mean, we had, I don't know, 10 quota carrying people. If you have hundred quota carrying people, it's probably Difficult to do that exercise.

[George Storm]

Yeah, no, but transparently, the logic or the fundamental logic behind it is not that different when it comes to. Because that would create the curve. What you're saying now. So best median and optimistic case would create a curve of probabilities. Because it's like when you say worst to realistic. Worst to realistic is not, if you look at it probabilistically, if you were to run for, let's say, Monte Carlo analysis.

[Thomas]

What is that?

[George Storm]

Monte Carlo analysis? Essentially a simulation of. The simplest way to put it is simulations of probabilities between one set point and another. What is the likelihood from very low on worst case to median to very high.

[Thomas]

Okay.

[George Storm]

And then you take in different inputs into that model and you say, so salesperson confidence is one thing, although I have to say that arbitrary weighting numbers are like stressing me out on a personal level. When I ask is like, what do you think? And it's like, yeah, but it's. I believe it will close with no data behind it. Besides, what a person believes gives me a bit of anxiety. But, like, you have these inputs, so you have historical data and you have personal confidence and you have market conditions. And then you say that, okay, I look at my probabilities, I set a range with a tail, a middle, and a head as a curve. And then I tell to my board that given these inputs, the highest probability in that curve is sort of somewhere in the middle. So the confidence of the forecast is the highest where the probability is highest mathematically, instead of me taking the inputs sort of in a black box and ending up with sort of an arbitrary number.

[Daniel]

Got it.

[George Storm]

And I'm spilling over to another topic now, but you gave me a really good hook, Daniel, talking about historical data. And this is another huge problem we have today with forecasting. You can't trust historical data. In today's market, it's almost mathematically impossible because the speed of the market. If you look at tech, right, we're talking to, we're speaking with people in SaaS now in this amazing community we're in. And AI is disrupting what we do completely. We talked about layoffs, we talked about interest rates being super high when you and I were young, talking about feature parity or competition or what your USPs are, what is possible out there in tech. You looked at it, you did competitive analysis once in December. You looked at it the December after. Nothing has really changed. Maybe somebody launched the feature, somebody acquired something else. And sort of the same right now you wake up to Legora and Lovable from one day to another. It's like my entire industry went away. Great. So looking at win rates a year back or even two, three years back, it doesn't make any sense. Or I mean, if you have a super stable company, you do a very niche thing that nobody else does that is impossible to replicate or copy or replace with AI, first of all, amazing for you and secondly, call me, but for the rest of us it's very unreliable.

[Thomas]

Yeah. And I mean also the historical data set must also depend a lot about, I mean the kind of business you have. If you have like 10 or 20 enterprise customers a year versus that you have 10,000 customers in a year, then I mean, it's much easier to go look at the history, maybe just for the last one or two months. But if you have big enterprise deals, then it must be much harder, right? Yes.

[George Storm]

No, it is much harder. Actually I would say that it is much harder regardless of the range, regardless of the portfolio, because it's, it's. We live in a, in a very unique era in my opinion, which is very, very exciting. It's also super stressful because I was both lucky and old enough to have sold stuff in during 2008 in the last huge event we all been through Covid, which to be honest, for SaaS, it wasn't that bad. So I'm not going to count that as a crisis event. But we had the financial crash in 2008 and then it was one parameter primarily that was problematic. You needed to mitigate risk, maybe play with discounting, compress your contract value a bit or your contract length a bit. It usually sort of worked out. Now you have so many different parameters. And I had people the last few months telling this, yeah, yeah, but like I only sell to manufacturing or enterprise or these things doesn't affect me. These things affect you guys in SaaS because of AI, it's you guys that are getting fired. It's only software. Well, that's not true because oil prices are up, interest rates are up, we have supply chain problems. So if you guys think that manufacturing companies don't face troublance, you're wrong. Yes, maybe they don't face troubling where they need to look at the balance sheet to say can we pay salaries? But they're not as volatile so the they can absorb more shocks, but that doesn't mean that they're sitting with the CFO every quarter and say, but what else can we buy if only we could add three more tools to our stack.

[Daniel]

I mean, I agree that there's like, you know, the world has significantly changed. Like you said, the pace of the world has changed. There's more noise. We all probably experience many new competitors popping up and buyers are buying software differently they were compared to how they used to buy it just a few years ago. So there's probably going to be hopefully a bunch of CROs and VP sales and CFOs listening to this. So, George, walk us through, what is your recommendation for them, given all this, given all the changes, how fast the market is, and potentially that it's not accurate the way we used to do it. Like how should we do it? Spell it out to us explicitly, how should we forecast? Walk us through the steps so we get this right. And hopefully it's also not an exercise that takes too much time every time. So once you have the system up in place or the process in place, I'm hoping or guessing it's some kind of a repeatable exercise. Then again, perfect.

[George Storm]

This was a really nice hook. Thank you. So the way that I look at this concept is essentially a forecast loop. So what you basically do is so you track and collect the data, you make an analysis, you take an action, then the action is getting measured, it informs the initial read and then it's an iterative process, not quarterly, but essentially you look at these impacts even weekly, depending on the business that you're in. So again, understand your situation, aggregate the data, interpret the data, decide what action to take depending on where you are, and then iterate in a continuous loop. And the reason I'm talking about, I started thinking about loops. I am a big fan of the winning by design concepts and they have been so Jaco and the team has been talking for quite a while now about these famous AI native companies and compound growth loops. And what usually broke my brain with these loops is that when they were talking about it is that but for companies like Lovable, these growth loops and the signals are since there is a quite strong PLG motion, or a big portion is a PLG motion, you have immediate inputs, right? So you see daily on dashboards, like what's happening? It's like, okay, great. If my sales cycles are 12 months long until the loop closes, I'm going to be either old or fired. So I need to track other things. I need to track micro actions and track my KPIs a lot or my numbers, every range of numbers a lot closer. So to make it a bit more concrete again in three stages and expand into a bit more of the concepts now. So we already Talked about range. I would suggest doing a Monte Carlo analysis like starting to look at probability and confidence in all of these numbers, not only the forecast number. Then the most important point for me is to start basing your forecast and your planning on regimes. And what I mean by regimes is essentially how the market behaves, the macro signals that we've been talking about. So I use three regimes is not that different to the concept that you mentioned, Daniel, but it has to do with macroeconomic parameters instead of our own signals internally in the company. So I forecast now under calm, turbulent and stormy weather or regimes and the regime change. Actually, although I would love to take credit and what I'm about to say about the market is fully my read and people can call me and ask me what I saw in my crystal ball. It is actually the World Economic Forum in the last end of last year, beginning of this year, that published a study with a few thousand risk experts that said that half of them said that they're looking at this year between turbulent and stormy weather.

[Thomas]

So that is something that you should keep track of. That should be a bookmark in your browser, check World Economic Forum to catch that metric.

[George Storm]

Yes, you should monitor and I mean if you look at it intuitively, should the CRO monitor the markets? The self explanatory answer is yes. However, and that is especially true in sas, we tend to live in a sort of our own bubble.

[Thomas]

Yeah. So do you think CROs are more working and looking internally rather than looking outwards towards the market and what's happening there? That's one of the fundamental problems in how we do forecast.

[George Storm]

Yes. This is what I started talking about before that we look at this very inside out either because I mean, look Thomas, transparently this is what we've been told to do. You've been told to own your number, to not bring excuses to affect. The number is just compiled by three static numbers that you affect. So it's number of top funnels, conversion to meetings, then you have ACV and then you calculate with win rate. Right. Technically all of these numbers you can affect to a degree. Again, the example that I brought before is you can multi thread all you want if the entire buying committee gets fired. I mean sure, you can sell to a whole other department that doesn't fit your icb. But like. Or if the company gets acquired, which I don't know if you have been seeing a lot of this. I definitely have and research that I did support is the amount of acquisitions, and especially acquisitions for distressed assets and mergers have increased dramatically the last year. And then there's very little you can do. And the point is not to bring excuses and say, yeah, but the market is. I can't swear on here, can I? The market is bad, I can't do anything. The weather is bad, I can't go outside. That's not the point. The point is how you model once you understand. So the second step is to understand the regime that you're operating under. I would suggest to start from turbulence. If you go on a column means that things will go based on historical data. And I'm willing to bet. What should I bet? I can bet half my library that there is very little probability that we operate in calm weather this year. So if you look at the regime and you say, okay, what does turbulent mean for me and for most of us in software? It means that deals will, in the best scenario stall because risk increases, people are getting fired or replaced, risk appetite goes down. So my sales cycle will probably increase and it will increase. And this is again the curve from 1.3x to 1.6x. So how do I look at my quarters? If I am to push pipeline a bit forward, then would I need to discount a bit? Because I am sitting with this, why wouldn't I build this in Claude debate, right? Maybe I need to discount a bit. So ACV will probably get compressed

[Thomas]

and

[George Storm]

then you look at the parameters under the regime you operate under. And then you need to forecast based on the fact that in high probability my metrics will get compressed or they will get affected to a degree. And once you do that, then you monitor ongoingly. I can tell you for instance, how I monitor this through recordings. I look at specific mentions of the signals that I am tracking and I started tracking these manually initially and I moved to an agentic way of doing it. From all sales calls and existing customers calls, are people mentioning somebody leaving the organization, new management coming in, replacing somebody else. Are they talking about acquisitions? Are they talking about budget freezes? Are they talking about mergers? In what markets do these mentions come in, in what frequency? And then you adapt your regime based on this market signals. Because I'm not just saying look at wef, the World Economic Forum and make your predictions. But it is a big indicator when thousands of economic risk experts telling you it's between bad and worse this year across industries, you should probably model on that. And then after monitoring the signals, you go into deciding what action to take. For instance, if you're seeing that your inbound flow is dying, or if you see that you increase your Sales cycles a lot. Then you look at the last of your levers and say oh, so how can I counteract this now? Because forecasting is not just lying down and accepting okay my win rate will fall. I might as well like submit my resignation to my board and look for another job. But how? If I have lower win rate then the one of the next step is one of the logical steps is to okay, then I will need to increase my top funnel, my early stage pipe to make my math still work. And these decisions need to be made on a rolling basis in a loop to be able to be. Because if you do this quarterly it's going to be too late. By the time that you realize that you're operating in stormy weather, your win rate has dropped from 20% to 13%. You've lost the quarter that you will need to report as a surprise to your board and then half of rust quarters the next quarter's pipe is the option is gone.

[Daniel]

That makes a lot of sense.

[George Storm]

Very long winded answer now.

[Daniel]

No, no, I think it makes a lot of sense and I'm just, just happy that we're sitting on this side and it was easier to forecast back in the good old days. I shouldn't say good old days because these are also great days now. George, it is a complex exercise if you may or like it's a complex debate. If somebody listening to this and feels like okay, I want to know more about this or for that matter I want to challenge George, where do they get hold of you? How do they get hold of you?

[George Storm]

LinkedIn. It's the simplest way. I'm trying to respond within two, three days on everything. Unless it starts with we help companies like blah blah blah to do xyz in which case I want. I'm sorry.

[Thomas]

Yeah and I think there is an article that also goes through this topic thoroughly. So I mean I think you can also debate in the comments there and let the discussion can move on. But if we look here it's a turbulent time, it's a lot of opportunities. So what do you say? What is in the future for enrich here? I won't say 24 hour months, let's say in the next three to six months.

[George Storm]

In the next. Okay, so the way that we, we look at the turbulence is that for every, every period like that there is an opportunity. So now we, we see this AI native way of fast growth loops and the main thing that we're thinking is a how can we help our icp? How can we help our customers navigate this Market. Thankfully, awareness is a very important topic. We're leaning quite heavily into allowing access to a lot of these data sets across the entire bowtie or across the entire funnel from top of funnel marketing to renewal. And we're looking to model our organization in a way that it is competitive with AI natives from a traditional B2B SaaS perspective with being able to react very fast in this type of changes. That includes product development, it includes my own forecasting in revenue and the tailoring and the tinkering that we do commercially, organizational changes, marketing and everything in between. So the way that we want to operate is that this model doesn't only apply to revenue, but it applies to the entire organization to be able to operate in that type of pace. So in two tracks product wise, leaning into how the market operates and helping our customers solve these problems, both with exposing data throughout the entire funnel and brand awareness and account progression and by developing how we operate.

[Thomas]

All right. As a company, you mentioned that you're hiring quite a lot at the moment. So if you got a wish, you get a person. What do you want?

[George Storm]

Oh, I need, I always need salespeople. It's I would say my by long and far least favorite part of this gig. Not the enriched gig, but the management gig is hiring and specifically hiring salespeople. It's one of these parameters that goes into these models which is very unpredictable and super, super volatile. So if you are looking for new opportunities on the sales side, also a good reason to reach out to me.

[Thomas]

Okay, great. And is there someone we should reach out to and have as a guest on the show here or a topic that you think we should cover?

[George Storm]

My first thought now would be Marcus. I think you've had him on before our CEO at Enrich. The second person that I would say that I think is very relevant given the market is the founder at Winning by Design, Jacko. So that would be my two in order. Yeah. Because I think especially this, the winning by Design approach is quite, is quite relevant and very, very time relevant modeling when it comes to how they, how they operate.

[Thomas]

Yeah, we have had Jako at a number of conferences. I don't really remember if we ever had him in the podcast any.

[Daniel]

I don't think we've had him in the podcast. He's spoken I think at probably three, four occasions across Europe here at our conferences, but I'm not sure, I don't think so.

[Thomas]

And as we have talked about, I mean a lot has happened and all of this AI stuff that we spoke about was, you know, before we did that. So definitely a lot to talk about there.

[Daniel]

Definitely. Definitely. George, thank you so much for joining us here today and expanding our minds on how the future forecasting can and should look, according to you. I'm happy again to say that as outsiders, we don't have to worry about it as much as you guys have to do. It's nice to sit on the sidelines for once. No, but truly, we live in a world that is changing and with that, we also have to adjust and adapt and so on. And I'm sure that we will figure this one out as well. So once again, super thanks to you and everybody listening here. If you want to pick up this conversation, George is your guy. So you find him Crownrich, you find him on LinkedIn.

[George Storm]

Perfect.

[Thomas]

See you around.

[Daniel]

Have a great day now.

[George Storm]

Thank you.

[Daniel]

All right, Thomas, I know you are a man of many talents. So what do you take away from this one here? Like, we also have obviously sales and revenue here. Like, are we going to forecast differently here? Are you going to suggest to me that even in our little business here that we should maybe think and look at things slightly differently?

[Thomas]

I thought you were about to say you're a man of many talents. Forecasting is not one of them, but I wouldn't say.

[Daniel]

I wouldn't say that. So, like, you don't know this, but Thomas has the secret talent. I don't know how he does it. One thing that is a really, really big unknown in our world, in our industry, and I don't think it's unique to our business, but anybody running events is, is the amount of tickets you go to sell and the amount of people that are going to show up at the actual event day. And I don't know how he does it, but Thomas has this magical feel, like already a few months before he has this idea that turns out to be pretty, pretty accurate. Pretty damn accurate on how many tickets we're gonna sell and how many are gonna show up. So hats off to you. So, like, no, on the contrary, you're very good at forecasting.

[Thomas]

Yeah. And it's not just a feeling. Maybe you don't think that out there that has in contact with us. Very hard to tell. But I'm a little bit of a statistics guy. So I have a system on how we follow up and how we predict and what numbers we follow. And it's always fun, especially when you see year by year, the sort of the tendencies. And it worked pretty well thus far, but. All right, so listening to today, I think one of the Things that I thought was interesting is you know, how to not just work on the internal numbers that you can control, but actually bring in the outside tendencies and so on and adjust your forecasting regarding to that. And that means also that as the world changes as fast as it does now, you need to increase sort of the cadence also of your forecasting in order for it to be a relevant number. So I think there's a lot to learn from that.

[Daniel]

Yeah. And also from my perspective, what I felt hit close to home was that when he said, yes, of course you can leverage the historical, historical data, it's a good basis and so on. But that's looking in the rare mirror. At least that's how I understood it. Like just because it was the truth last year or previous year or previous quarters, it doesn't mean that that is going to hold up in the Future. And I 100% agree with that because as the world changes, we know buying cycles are potentially longer, people buy different way. Maybe the numbers we have from the past, the hit rates and win rates and so on, they might not be accurate. So having this perspective where we don't just look from an inside out perspective, you know, we should have an element, however that looks now, I don't know exactly, to bring in an outside perspective like how do we bridge the past with the future and find a way where our forecast becomes much more accurate. And, and yeah, I think it's exciting times out there and let's see what's going to happen. But it's certainly moving fast now out there and we're just happy to be part of the ride.

[Thomas]

Absolutely. And also what I think was nice, George told us that many of these thoughts and ideas were a result of conversation at the sassiest executive dinner that we had. And if you're interested to be a part of one of these forums, if you're a VP or higher at the B2B SaaS company in Europe, above 2 million euros in ARR, most companies are somewhere in between 2 and 200. Then you can head over to executive.sasius.com or if you're CEO, you can go to [e-mail] and you can apply for the networks. A great way of connecting with peers and get some extra insights and help with your business. And I think with that, thank you for listening. We'll be soon back with another episode and as we said before, if you're interested in joining us for Sassyest Paris or Sassiest Munich, please reach out. You find all full information. [e-mail] and their respective websites. So thank you so much for listening and see you around.

[Daniel]

Take care.