Intro: Broadcasting live from the Business RadioX studio in Atlanta, Georgia. It’s time for Atlanta Business Radio, brought to you by Kennesaw State University’s Executive MBA program, the accelerated degree program for working professionals looking to advance their career and enhance their leadership skills. And now, here’s your host.

Lee Kantor: Lee Kantor here, broadcasting live from Fintech South 2024 at the Woodruff Arts Center. So excited to be talking to my guest today. Right now we have Nate Kaemingk with Better Forecasting. Welcome.

Nate Kaemingk: Hey, thanks for having me.

Lee Kantor: Well, I’m excited to learn what you’re up to. Tell us a little bit about Better Forecasting.

Nate Kaemingk: Yeah. So we have written a forecasting AI specifically for mid-market finance teams. So that’s going to be companies anywhere from 10 million up to $1 billion a year in revenue, and it’s written specifically to help with annual forecasting process. To make it a lot easier. I can go into customers and you tell me how much to.

Lee Kantor: Well, I just I’m just trying to get an idea for our listeners to understand what it is you’re doing and how you’re serving folks. Yeah, yeah. Go as deep as you’d like. All right.

Nate Kaemingk: Sounds good. Well, so the three, the most common reason we get phone calls or people are trying to improve their business is because they’re tired of what we call the annual guest process. And that’s where you take last year’s numbers. You kind of try to guess what’s going to happen next year. You know, we’ve all been through that process. Every corporation I’ve worked for has done that process, and it works on until it doesn’t. And so but.

Lee Kantor: Does it really.

Nate Kaemingk: Work? No it doesn’t. That’s actually the reason.

Lee Kantor: What’s the accuracy percentage of people’s forecasting I’m.

Nate Kaemingk: I’m impressed when people can get within 10% of what they said they were going to be able to do. Like if you got.

Lee Kantor: 10%, you’re high fiving.

Nate Kaemingk: Yeah, exactly. Exactly. And that and then I’ve had, um, a recent company I can think of that called us. They said, you know, hey, for the last three years we have been off by 35%.

Lee Kantor: Just a third. That’s all.

Nate Kaemingk: Yeah, just a third. I mean, how do you run your business on that, like. And so so that’s one of the main problems. The next one is the classic, you know, hey, we’re running out of cash, but we’re profitable. What’s going on. Right. And so we will try to work with people on terms and what they can change. And then the third one is just of course, you know, the executive is about to make some major strategic decisions and he just wants to have some support like, okay, what are some unintended consequences that I can’t see yet. So we will help build models and our AI will build models for that. Um, companies solve that today. I mean, anybody in a corporation in finance will know this, but the companies typically will solve that today by hiring a person that does what’s called financial planning and analysis. And they’ll show up at the executive session with their 57 tab Excel spreadsheet. And they will try to answer any of the questions that are thrown their way during that session. Now, now, what you have to keep in mind is the meeting isn’t the problem. It’s how long it took to build that 57 tab Excel spreadsheet, and the fact that it won’t answer half the questions that are thrown at them that day anyways. And so what we’ve done is we’ve shortchanged that process. When I was at a previous role about a decade ago, it took us three man years, nine calendar months to show up at that meeting. And we still didn’t get it all right. We still had to go back and keep fixing it. And so what our tool does now is it takes that entire months long process and turns it into something that takes hours instead of months. And then there’s the annual rolling forecast. There’s actually a company I can think of. I can’t name names, but I can, um, there are $3 billion a year company.

Lee Kantor: What’s a rhyme.

Nate Kaemingk: With, uh, uh, they’re in agriculture, that’s all, as far as I can go, because they’re big enough, but, um, so. And they don’t they only do their forecast twice a year because it takes too long to do the update. So they just don’t even get any value out of it.

Lee Kantor: Why bother even doing so?

Nate Kaemingk: Why bother? Because it’s going to be by the time we get the updated forecast. Right. Exactly. And so what we that process is typically best case two days and worst case six weeks like we talked about. That takes minutes in our AI to do that update every single month.

Lee Kantor: Now in your AI, are you taking kind of industry information or are you taking just the specifics of this individual company? How do you go about building the forecasting model?

Nate Kaemingk: Fantastic question. So so we will start with the company’s financials. And that’ll be your balance sheet your profit and loss. You know GAAP standard accounting. So I love accountants.

Lee Kantor: You’re getting as much accounting data as you can as it just do you want like kind of historic. You want the whole shebang or. Yeah. Yeah. As much as they’ll give you, you’ll take.

Nate Kaemingk: Monthly financial statements back as far as you’ll give them to me. And but the full you know, here’s, here’s what the balance sheet close was as of the end of January 2024. I need the whole piano, the whole balance sheet. And with that, and we do that for every single month back in history with that.

Lee Kantor: And then you layer in, you know, kind of the industry standards and benchmarks from other, you know, from all the players. So you’re not just seeing theirs.

Nate Kaemingk: Well, so we actually I’ll kind of walk through that process. It’s actually a three step process. So the first thing we do is we take their historical data and we establish trends. And the reason that works is there’s a little bit of a psychological reason for that. If you don’t if you don’t recognize that 95% of the thoughts you had today, you had yesterday, sure. How to tie your shoe, how to drive your car, how to, you know, so we’re creatures of habit. And it’s actually our brains are designed to to not use high brain power. Right. They want to think about you know, that makes sense for.

Lee Kantor: They need to pay attention to danger. They don’t have to worry about how to tie their shoes. They already know how to tie their shoes. Exactly.

Nate Kaemingk: And so, so because we our brains are biochemically wired to create habits, that happens in our work. It happens in our business, it happens in the stuff that I buy on the way If I’m driving to work one day, I’m going to pretty much stop at the same gas station every time. Maybe I would change if there was a better price somewhere, but I’m pretty much going to stop at the same gas station or the same grocery store. I’ll buy the same flowers from my wife. You know, that’s all habit stuff. So we, as forecasters, will take advantage of the fact that human beings are creatures of habit. So when we’re doing a historical trends based forecast, we’re actually establishing a foundational baseline. Like this is what’s normal, right. And the only time and now there will be slight changes. You know, people change a couple of habits a year. There’s even entire industries written around how to help you change your habits in a healthy way. So we will capture those changes. That’s why we have to do the rolling forecast. We every single month, we’re going to expect to have 3 to 5% change in what happened from the previous year and capture that and keep moving it forward. The second bucket is the sales funnel. And so that’s the you know how many people hit our website. It’s all internal data. You notice I’m not saying anything about external data quite yet.

Lee Kantor: So so far it’s all internal.

Nate Kaemingk: Yep. And so the second thing would be, you know, how many conversations did you have? Did your sales team go to conferences? Did they fill in their CRM, their HubSpot, their Salesforce, or whatever you’re using? That is really good at giving us what is about to.

Lee Kantor: Change, right? What’s going to happen tomorrow?

Nate Kaemingk: What’s the. Yeah. So from the trend you can establish not just the most likely, but you can establish a high range of probability and a low range of probability. And then you use the sales funnel data to show well which direction are we heading. Are we on the high end? Are we on the low end. Right. And then once that’s all established, then we go to the outside market factors. We start looking at we actually pull in weather data. We pull in. The Bureau of Labor Statistics has a lot of, you know, you know, in the construction industry labor cost is a massive problem right now. Right.

Lee Kantor: And so supply chain issues, anything that’s happening, maybe there’s a pandemic, you know.

Nate Kaemingk: Something like that happens.

Lee Kantor: Anything can happen.

Nate Kaemingk: Or, you know, a ship could crash in the canal. Right now.

Lee Kantor: It’s blocked for a.

Nate Kaemingk: Year, right? Absolutely. And so so then we start trying to because because the most impactful thing to a business is what it does itself. We always want to look at the market. The only time the outside market really matters for a business is when they get large enough that it really matters. So we’re talking 10 to 30% of total market share before the outside factor is absolutely. You know, it’s like there’s nothing they can do internally to change what the outside market will do to them. That’s not always true. So once we do that, what we’re looking for is okay, what can’t be explained by the sales funnel, what can’t be explained by history. And if there’s any noise left over, then we go look for, well, there was a pandemic or a ship crashed or, you know, any of these events. We can.

Lee Kantor: Think of these.

Nate Kaemingk: Outliers. Yeah, exactly.

Lee Kantor: So then, um, so how did this idea come about? What was the genesis of the. Hey, I can come up with a better mousetrap for this.

Nate Kaemingk: Yeah, well, I just I came at this weird. I mean, I actually started out as a mechanical engineer, and I learned a whole bunch of math and statistics. We had an engineering problem I had to solve, and it was $10,000 per data point, and it was a couple of days of work to get a single data point. Now, this was when $10,000 was worth something, right? Um, and and so because of that, I learned a very specific subset of niche math known as inferential statistics for small data sets. And and it sounds horrible. And that’s I think it’s fantastic. But that’s my problem, not yours. So, um, because of that, when I went and did my MBA, all the bankers had me do their homework, as I like to say it or otherwise. They said, hey, we’ve never seen anyone do this before. Let’s have you start. So I kind of figured out I had something unique. Then I had a chance to go apply it at corporate. I worked for a fortune 500 company and got to do forecasting for them, and I had a lot of people come back to me like, you’re you’re approaching this in such a new way that handles risk factors. We’ve never seen anyone figure out how to handle before. And it was because of that background. Eventually, um left that fortune 500 company and I started doing this. I was I started doing this as a freelancer, and eventually it turned into my company because people liked it and they kept wanting to pay me for it.

Lee Kantor: And and you’re getting a better result than being off by a third?

Nate Kaemingk: Absolutely. Yes. If I, if I what’s amazing is how many people keep their jobs when they’re off by that far. And they, you know, either.

Lee Kantor: The weathermen keep their jobs or they’re like barely 5050.

Nate Kaemingk: I had a it’s funny when I say I do forecasting, I have to figure out how to tell people I’m not a weatherman.

Lee Kantor: Well, Connie, you.

Nate Kaemingk: Are.

Lee Kantor: A different kind of way.

Nate Kaemingk: I can tell you what weather will do to your business, but I can’t forecast what the weather is, so. Yeah.

Lee Kantor: So now you were part of the Fintech South Innovation challenge? Yeah, I.

Nate Kaemingk: Was, I was.

Lee Kantor: How was that experience for you? Oh, it was fantastic.

Nate Kaemingk: So they did a really good job. They they had a list of a whole bunch of companies that applied out of that list. They picked ten and had, you know, industry experts come in and talk to us about various topics, pitching investors if you’re interested in and that kind of thing. And then I got selected for the top three, which was amazing. And because I was in the top three, I got to pitch on the main stage here at fintech. So and the best I didn’t win good agriculture. One shout out to them. They did a fantastic job.

Lee Kantor: How are they at forecasting?

Nate Kaemingk: I actually don’t know. That’s a good question. Um, we’ll have to ask. Uh, so, so but what has been amazing about it is the number of companies that have been like, oh, I have that problem. You know, I actually had a I met somebody in the lobby and they pulled me aside and they were like, Nate, I know, I know the guy’s name that you’re talking about. You’re talking about this guy that stuck with the 57 tab Excel spreadsheet and got, heaven forbid, he gets hit by a bus because we’re we’re we’re screwed if that happens. And so we’re, we’re trying to de-risk that critical process and make it seamless.

Lee Kantor: So now is there a niche for your product.

Nate Kaemingk: Um, so so they’re.

Lee Kantor: Still learning that.

Nate Kaemingk: We’re still learning it. So the industries we’ve had we’ve had success in about five industries so far. But that’s mainly because we haven’t found any industry we haven’t been successful in. But, you know, we’ve had the most experience in construction and then in services. I like the non-sexy, repeatable businesses that like their great customers for what we’re doing because they’re growing year over year and they’re there anyway. So construction services, consumer product groups, some healthcare and then manufacturing are the ones that we’ve done the most work with.

Lee Kantor: Now, you said you’re you do better than the 35% person. What what is your kind of range of accuracy in your forecasting. Good.

Nate Kaemingk: Good question. So we’re still getting the 90 to 95% on average. But one of the unique things that we’re doing is we can tell you which month we’re going to be accurate and which one we’re not going to be accurate. And that’s very different. The industry standard benchmark is forecast accuracy. And I’m doing air quotes. I know you can’t see me do that on the radio. But that’s an average error for the entire year. Well if you’re 95% 5% correct for 12 months. That means one out of those 12 months, you’ll be off by 15 to 20%, and you still get to say you’re 95% correct. The difference in ours is we can actually tell you which month we’re not going to be correct. We can tell you that in August we’re going to be plus or -2%, and in December we’re going to be plus or -20. And as much as a forecaster wants to say I’m always correct as a business manager, it’s actually more important that you understand when there’s uncertainty in the forecast and what.

Lee Kantor: The limitations are. Exactly.

Nate Kaemingk: And so for the businesses that that that is a specific business that I’m thinking of that had plus or -1 or 2% in August, their staffing plan, their go to market plan, their what we’re going to do. We just nailed it. Like, okay, we know where it’s going to happen. We’re going to go do it. Just just get the work done. But for the December plan, when it came to September, we looked at December and we said, hey, we’re pretty sure we’re going to be on the low end of this, but we’re going to write a scalable execution plan, because as we get into the month, we know that we’re going to start to recognize, like so. So you staff your business differently. If you know that there’s uncertainty, you staff your you change. The way you’re operating plan going into it is. And it was actually very beneficial for them for us to even though we couldn’t nail it exactly, we could at least tell them the range of possibilities. And because of that, they wrote a business plan and were very successful in that month, no matter where it landed in the forecast. Right. Because they were prepared?

Lee Kantor: Yes. Now, if somebody wants to learn more, have a more substantive conversation with you or somebody on the team, what is the website?

Nate Kaemingk: Yeah. Well, besides just sending me a check, um, just so our website is, is better forecasting.com. So come and come and check us out. Yeah. Better forecasting.com.

Lee Kantor: Well Nate, thank you so much for sharing your story today. You’re doing important work and we appreciate you.

Nate Kaemingk: Thank you for having me I’m excited to be here. Thank you. All right.

Lee Kantor: This is Lee Kantor. Uh, we’ll be back in a few. At Fintech South 2024.