Latest / Exit Algorithms / How Investors Evaluate Your Business Before Writing a Check with Kim Lundberg (#69)
Transcript
- Pete Vera, Exit Algorithms: Welcome to exit algorithms, the podcast where we decode what it really takes to unlock growth, streamline operations, and prepare your business for a high value exit. I'm your host Pete Vera. And today I'm joined by Kim Lundberg. He's a director of tech and venture lending at IFO, Denmark's export and investment fund, where he deploys high risk, long-term loans for up to 25 million euros in Danish startups and scale ups. and actively manages a portfolio of 30 of Denmark's most promising high growth companies. Kim, great to have you on the show today. Welcome to the podcast. Kim Lundberg: Thank you, Pete. Been looking forward to this. Pete Vera, Exit Algorithms: Yeah, same here. Yeah, can you start off and share bit about your background and ⁓ journey in banking and investing? I'd love to hear a little bit more about your career. Kim Lundberg: Sure, Thanks for having me. ⁓ professionally, I grew up in corporate banking years ago in a large Danish bank doing traditional banking. ⁓ And then... ⁓ Fast forward to 2017, joined IFO that you mentioned. IFO is a sovereign fund and a national promotional bank in Denmark. We manage, I think, billion Danish. So that's... in the that would be like 12 billion ⁓ US dollars. more. The double of that. Sorry. So ⁓ we are like 500 employees and doing businesses towards ⁓ a broad spectrum of companies ranging from early stage startups, ⁓ both loan and equity, to scale-ups, to traditional bankable companies, ⁓ SMEs, but also doing different types of guarantees towards big corporates with activities outside of Denmark, most often they're counterparties. would do large transaction and finance specific ⁓ deals. Pete Vera, Exit Algorithms: Yeah, awesome. Really, really exciting. What are some of the things you look for before you deploy capital for IFO? Kim Lundberg: So in my specific niche area, which is ⁓ doing loan financing, lending towards scale up companies still burning cash, some of the core... arguments for doing loans for that type of company which a normal traditional bank would be hesitant on doing. Some of the core arguments are looking at ⁓ the data around ⁓ buying and keeping their customers so their retention dynamics is very important for us. Most often also their ability to raise more equity ⁓ as they rely on ⁓ having ⁓ ongoing liquidity cash into the company while they burn cash. And most often they would have investors covering some of that. But also besides those more hard data points, ⁓ The softer ones also come into play looking at the team. The people managing this company is very important that we believe in them. Pete Vera, Exit Algorithms: Mmm. Sure. Yeah. What is the vetting process of a business? How do you assess their culture and some of those aspects that you like beyond just financial data? Kim Lundberg: Yeah, so very good question. ⁓ for the smaller loans or the normal loans we do, ⁓ it's ⁓ the frontline people like me, would most often have a small deal team around me doing a transaction. would of, naturally we would meet the management. ⁓ Maybe take a tour around ⁓ the office at the company. Already by that you would have a lot of feel of how it is surrounding the company. But also the people, the management, when you meet them. Over the years ⁓ I've been more more confident in that this first impression that I get, actually most often it's the truth. ⁓ So when you've... Pete Vera, Exit Algorithms: Mmm. Kim Lundberg: met people for the first time, looked them into their eyes and had the first conversation with them. Over the first 10-20 minutes, you have this impression. ⁓ Are they good at what they do? ⁓ Are they good at managing other people? ⁓ Do we believe that they are capable of setting ⁓ a good, healthy, successful culture? Most often that sticks those first 10-20 minutes. ⁓ If we do larger deals and also where we have big jumps, it could be an ⁓ &A deal where they would buy, acquire another company. Something big happens where we have a management... Pete Vera, Exit Algorithms: Mm. Kim Lundberg: that hasn't ⁓ historically, we haven't seen them do that specific action or managing ⁓ whatever jump it might be. Then we could ⁓ put into play our, we have internally, consultants doing an HR management doodling process. So we would try to... ⁓ Pete Vera, Exit Algorithms: Okay. Kim Lundberg: to crawl into people's heads and put a number, so to say, on how solid they are in managing this company and execute ⁓ the future plans ahead of them. And also part of the process, digital management process is also ⁓ trying to sort out how they work together. So not only like... couple of key C-suite level persons individually, but also how they work together. That's quite interesting. Pete Vera, Exit Algorithms: Yeah, wow, quite... Very interesting, very, it... Kim Lundberg: And most often also the outcomes and the analysis and the discussions around it, most often it's also ⁓ quite interesting for the company to dive into. ⁓ They get a lot of value out of it as well. Pete Vera, Exit Algorithms: Sure, they probably learned a bit about their own company through that process. Yeah, very involved. What are some things businesses should do to prepare for an investment, to be investor ready? Kim Lundberg: Might be. Might be. Yeah, so good question. ⁓ It's always very good ⁓ to... So the financial model... ⁓ So when a lender or also an investor would dive into a potential case, ⁓ one of the things that we love to crunch, ⁓ that is the financial model. ⁓ The bigger, the better. That's not quite true. the more relevant and the deeper and more correct and... the more it embraces the full complete picture way out in time, the better. So ⁓ when we engage with the companies early on, ⁓ naturally they wouldn't have this in place from the very beginning. So it's also our role to try and nurse and notch for them to ongoingly set up ⁓ a ⁓ proper financial model. ⁓ with all the assumptions behind it, with all the data, showed that both they want to use themselves internally at the company, but also the stakeholders around the company, the board, investor and lender as I am. ⁓ When you receive, it happens ⁓ from time to time that you get hold of a really solid financial model, then it's just much easier to... to get hold of the company and to do the analysis that would argue why should we do this loan and how should we structure it. So getting hold of the numbers, the data in the company and presenting them ⁓ in a good way, that's very important. Pete Vera, Exit Algorithms: Yeah, for sure. Yeah. So clean, very clean financials, very organized. They can prove that the revenue is recurring and will continue to grow in the future, right? Kim Lundberg: Yeah, and I would say like actually like the layer behind the financials layer behind the revenue. So ⁓ that's how the customers act. ⁓ like the raw some of the raw data, for instance, that would be like a cohort picture of each and every customer. When would they join the company? How long did they stay? Did you do any upsell towards them? So it's back to this. ⁓ retention dynamics that I mentioned earlier, we need to have trust that the company would also have a cash flow a year out, two year out, five years out actually, because the loans we structure are most often five to six years loans. So we should believe that the customers will stay with the company ⁓ and are willing to un- ongoingly pay those subscription revenues. Pete Vera, Exit Algorithms: Yeah, how do you find or how do you what do you look for to ensure you know they have a healthy relationship with the customers? it you know is it contracts or what kind of what kind of business do to be on contracts to ensure you know the customer will stay with them? Kim Lundberg: So naturally we would also dive into the contracts. How are they structured? Are they one-year contracts, two-year, three-year? ⁓ Most often it's one to three-year contracts in this classical B2B SaaS company with 12 months paid upfront. ⁓ But also one thing is the legal side of the customer relationship ⁓ that ⁓ our customers have. It's also very important to get hold of this product that they deliver, this service that they deliver ⁓ and demand a price for. Does this balance ⁓ in the eye of their customers? So the perceived value... ⁓ Does that make sense? Are the customers happy? So we could have maybe NPS data. ⁓ We could also ⁓ for many companies, it's also relevant to get hold of the TrustPilot score. I don't know if it's more Danish or Nordic thing. TrustPilot is originally a Danish startup. ⁓ for more than a decade ago, but that's like the public view of how happy are the customers. And you can get good feel of how happy customers are with the company's services products. Just by that, it's very easy to look up. Pete Vera, Exit Algorithms: Yeah. ⁓ that makes a lot of sense. A company getting ready to go, you know, to get for sale or for investment and taking on a loan. Yeah. Managing all those things and making sure your, you know, your online presence is good. Cause that's probably one of the things, first things you'd look at, right? Is those reviews. Kim Lundberg: It could be, yeah. A lender could also do ⁓ customer interviews, but I think most often with the companies that I lend to, ⁓ they would have 500,000, thousands of customers. It wouldn't make sense to just do like a one spot interview with a few of their clients. ⁓ It's much more important to get a full view of their total portfolio and how it develops. Pete Vera, Exit Algorithms: Gotcha. Yeah. Yeah. And we talked a little bit on the pre-show about, you're managing 30 portfolio companies and they're all growing and scaling. I was curious, do you see any commonalities between the companies that, you know, that really take off and grow? What are they doing right that other companies aren't? Kim Lundberg: Good question. So I think I would mention ⁓ two specific things. ⁓ First one is very much attached to this thing around how you perceive the management. ⁓ So I think... Often I see that the very successful companies, they have a management that is first of all very competent, very skilled at what they do. Often they've tried it before, like starting and growing a company. ⁓ Maybe they weren't successful with the first one, ⁓ but they have experience from earlier on. And then combined with this very solid skills and personality, they are quite humble in their approach, ⁓ in their communication. So... It will always be ⁓ a delight to have this collaboration and relationship with them ⁓ in the daily communication, actually. So very competent skilled person with a humble approach. That's often a very good recipe. The other thing I would say is ⁓ I think often I've seen that the very successful ⁓ scale-ups, are the ones... Obviously they're doing good because they're able to raise equity, but they often do it ⁓ very early and they take a lot of equity on. So they would be almost overfunded, some would say. ⁓ They have more cash on their balance than their business plan would require them to have. They have a lot of buffer. So they would, when a certain opportunity arises equity-wise, they would grab it ⁓ and then they would accept ⁓ a large quantum intake of equity and then ⁓ accept also to deliver more of the cap table, to be more diluted. But you're always, by doing that, you're never in stress on the cash. ⁓ You could say the opposite, the opposite position. I've also seen that sometimes. When people, they try to ⁓ optimize their valuation, they try to wait until the last second to raise those money. Pete Vera, Exit Algorithms: Mm. Kim Lundberg: it always gets stressed and when an investor sense that you're on limit, maybe in that last hour, they would maybe back a bit off and try to get more out of the deal. The terms would be ⁓ reduced or more bad or something like when you try to go to the limit, it brings on a lot of stress. Pete Vera, Exit Algorithms: Yeah. Hmm. Kim Lundberg: the whole organization, it's much harder, much more difficult ⁓ to initiate ⁓ new large development projects ⁓ or anything that would require cash. ⁓ Just hiring people ⁓ gets more complicated because you don't know ⁓ if you have cash to survive in three months time. Pete Vera, Exit Algorithms: Mm. Kim Lundberg: So that's the opposite position. Always be early and be up front ⁓ racing and race more than sufficient. Pete Vera, Exit Algorithms: Yeah, really good advice. ⁓ Fascinating too. I think that's a conflict a lot of businesses go through is when to take on ⁓ debt or when to give up equity. The timing, think that's a really difficult rope to walk, balance to strike. ⁓ I was just, yeah, it's interesting. ⁓ Kim Lundberg: And people often forget the stress that they put on their organization trying to optimize ⁓ cap table valuation. Pete Vera, Exit Algorithms: Yeah, yeah, that's true. Yeah, your working capital is running short and yeah, you're in a bit of a cash crunch that's no good, not a good spot. I just watched a documentary about DeepMind ⁓ and yeah, thought that his philosophy was really interesting. Google eventually bought him, bought them for like 400 million and he's like, I know I'm giving up a lot of, you know, it's gonna be worth way more than this in the future. But he's like, for the sake of research and improving AI or AGI, he's like, it's worth it for me to just accept this now and give up equity. ⁓ But it's interesting. Kim Lundberg: Very, very. Pete Vera, Exit Algorithms: Yeah, I'm curious, do you see any big common mistakes that companies make ⁓ with respect to financing their business that could affect their ability to raise or borrow again in the future? Kim Lundberg: The one that I just mentioned would be one of the answers I would provide to that question obviously. ⁓ But I think in general ⁓ I would put into light what is relevant in all relationships with your external stakeholders. ⁓ Inform them, ⁓ keep them up to date. ⁓ nurse the relationship. ⁓ If something happens ⁓ and you have to manage ⁓ a situation quickly around cash or restructuring alone or whatever, ⁓ if the lender or if it's an investor, ⁓ either way, ⁓ if they're up to speed on where you are, it's much easier for them to... ⁓ react quickly. ⁓ And if you could also put it even further and say, if you were always ⁓ providing ⁓ their information and showing them where you are, inviting them to deliver feedback, it's also easier for them to... ⁓ ⁓ to calibrate with you along the way and maybe the feedback could be very useful for you in operating the business. ⁓ So keeping your stakeholders up to speed, delivering that ⁓ brilliant ⁓ reporting ongoingly, that's something I would nudge for. ⁓ And then to your question, Pete. ⁓ mistakes. ⁓ There is like when you build a company, always hire people, you hire people, you build the organization, you frame one team, you frame another team. ⁓ There's this thing around, well, the first 20 people, they're the ones setting out the culture. So obviously be very aware of who you hire in the beginning and that they should be able to carry the culture along the way. One mistake, that's also something we look for, is that, well, somewhere along the road, you need to lay off people. ⁓ Pete Vera, Exit Algorithms: Okay. Kim Lundberg: How are you able to do that? Another thing is the founder CEO that started the company grew it to 20 to 50 people, maybe 200 people. Maybe that person is very strong at doing that, but maybe the company is better off by having another CEO scaling from 100 to 1,000 people. Pete Vera, Exit Algorithms: Mmm. Kim Lundberg: Maybe that founder CEO also ⁓ leverages more energy ⁓ in another role than being a CEO when you cross, let's say, 100 people in the organization. How is that person aware of that? ⁓ That's also important. Pete Vera, Exit Algorithms: Yeah, really good points. ⁓ Love that insight. Definitely, Grant. And I love your continuous emphasis on the team as well. think that's really important. Yeah, and I want to open up the can of worms. Probably the topic for today's call is AI. ⁓ I know you're on the front end, the tip of the spear with AI automation and SaaS companies. ⁓ I'm just curious, how are you seeing AI being used most effectively and how do you see it affecting your industry? Kim Lundberg: Yes, ⁓ so we could talk about this subject for hours, guess. But obviously it's something that we, also in my team, ⁓ follow very much. Both how do we adopt it ourselves and use it ourselves, but also what does it mean to the companies that we ⁓ finance, to the companies we have in our portfolio. I think for years now we've heard this ⁓ ⁓ that SAS is dead, B2B SAS, ⁓ AI will eat it. ⁓ I don't think it's that easily framed. ⁓ We do see some involvement that is important and that is if you have like a horizontal business ⁓ with a non-complex product, ⁓ just doing integrations from some other ⁓ software services and then ⁓ binding that together in the product that you deliver, maybe that doesn't have the same relevance as a standalone product in the market as it had five years ago. ⁓ If you have a product that relies on big industry knowledge on a big data pool that you've collected over the years, that's something that AI just, they can't just ⁓ replicate that. ⁓ They can leverage it off, but they can't replicate it. So a company having this ⁓ vertical ⁓ position I don't see AI, so to say, eating that or killing this kind of SaaS company. And then there is the companies that's still like horizontal, as I mentioned before, been in the market for years, having a great large customer portfolio, ⁓ happy customers, ⁓ paying each month or each year. ⁓ in my mind, they would still stick to having that software service. If the perceived value and the price is somewhat balanced, why should they try to build something themselves with an AI agent or another company ⁓ able to build it much cheaper, obviously, this company did five years ago, for instance. they still know their customers very well. And that's their big value and having the customers on board already. think a huge part of that customer portfolio will still be with that company next year and in five years and maybe in ten years. ⁓ Maybe they can't collect the same equity as they could before the multiples have been going down on that type of company. So they should be able to carry themselves. ⁓ Pete Vera, Exit Algorithms: Mm. Kim Lundberg: with positive cash flows, they could be able to absorb some debt, might be. ⁓ But the multiples for, the investment multiples for that type of company has been going one way. And I think ⁓ the more vertical ⁓ B2B SaaS company with a lot of ⁓ interesting knowledge and a big data pool might be, ⁓ this is still. Pete Vera, Exit Algorithms: Mm. Kim Lundberg: interesting for investors and multiples are not ⁓ going in the same way as the other. Thereby, they can still do big investments in growing the company, in developing more on their product, burning cash, because they're able to ⁓ equity. ⁓ So I see... Pete Vera, Exit Algorithms: Good. Kim Lundberg: like a divided path in this B2B SaaS world when we talk about AI. I visited a company last week, ⁓ one of the smaller ones in my portfolio, they just mentioned, I think there were 25 employees at this point, they just ⁓ exchanged, I think, six, seven, eight. ⁓ QA people with AI agents. They couldn't do it one-to-one, so some of the tasks they had to put back to the software engineers, but a majority of what those roles did before, they could have an AI agent to do that instead. So that's a big part of the company if they go from, say, 32 to 25 people, right? Pete Vera, Exit Algorithms: Love. Kim Lundberg: That's massive. And then I think also an important thing here is that, well, the smaller, younger companies, they're much more able to adopt AI than the bigger corporates. Now, I just mentioned how we're trying to utilize AI ourselves. We are a larger company ⁓ with much more legacy. ⁓ So I believe that the smaller, more flexible companies, they... Pete Vera, Exit Algorithms: Yeah. Kim Lundberg: they would be much faster at embracing AI and leveraging on the value that it brings. Pete Vera, Exit Algorithms: Mm-hmm. Yeah, and that's definitely one advantage rather than trying to retrofit it, you know, into the business with existing systems already. Yeah, that's awesome. Now, really, really great answer. You know, you've been at IFO before AI really came onto the scene. ⁓ How has it affected, has it affected any of your portfolio companies, like, negatively or positively for that matter? Kim Lundberg: I would say it's back to this divided path that I would say in general overall it's until now it's not a big revolution but there is an evolution ongoing and there is this path split where some companies are and will be challenged because ⁓ their product isn't so to say deep enough ⁓ It can be replaced and by much faster ⁓ machinery today with AI. ⁓ But the companies ⁓ having ⁓ a ⁓ product and a service that is tied up to their big domain knowledge and to a big data pool, well, they continue to grow with high growth rates. ⁓ and they continue to go into new markets. ⁓ And maybe they're actually able to go faster now because back to this example of ⁓ lowering the costs for some kind of roles in the organization, well, ⁓ obviously there are different areas where you can cut some costs in the organization. ⁓ Yeah. Pete Vera, Exit Algorithms: Yeah, great answer and so many amazing takeaways, good ⁓ nuggets of wisdom, I think, for business owners on this call. So thank you so much for your time, Kim. Where's the best place listeners can find you and hear about the work you're doing? Kim Lundberg: ⁓ Good question. ⁓ I think I'm quite present at LinkedIn. ⁓ Feel free to reach out. Pete Vera, Exit Algorithms: Sounds good. Yeah. I'll leave that on the show notes. Thank you for coming on the show today, Kim. Great talking to you. Kim Lundberg: Likewise Pete, thank you for having me.