The Exchanges

Q So can you explain how you stumbled upon the negative cash conversion cycle and why that was so powerful?

A Yeah, so, you know, we didn't have any capital, right? And so, uh, you know, what, what we, what we figured out was that if we could dramatically, uh, shrink, um, our inventory and get paid from our customers faster and, you know, uh, maybe not pay our suppliers, you know, instantly pay them a little bit later, then If you're growing and you have a negative cash conversion cycle, you actually generate a lot of cash. And so, you don't need as much capital to raise to be able to grow the company. You have a high return on capital. So, we started looking at the business that way. And of course, we also, uh, there was this, um, really interesting thing where our competitors, who didn't really understand what we were doing, they had these elongated supply chains. They had distributors and dealers, and so they would have, you know, like, 90 days of collective inventory from the time that they actually made the product to when it actually got to the customer. And you could actually understand this because if you opened up the computers, the chips had dates on them that showed the weeks they were made.

AI assessment note: “we didn't have any capital, right? And so, what we figured out was”

Q Yeah, Zach told me, he's like, he'll call me at, like, five a.m., and he was like, I have an idea. Like, we should do this product or this acquisition or whatever. He's just like, he just can't help himself. And I asked him, I go, uh, what would get him to stop? He's like, you have to kill him. What made you decide to write the book?

A You know, we, we had, we had gone through a whole lot, uh, with the going private and buying EMC and VMware and, There just been so much that happened. I wanted to kind of document it, and it was during COVID. I had some time to start, started writing the stuff down, and it felt like a logical place to, ah, sort of capture everything that, that had happened. You know, one of the main reasons I wrote it was for our team inside the company, because I, you know, want them to understand, uh, you know, how we think about the business and where it came from, and, you know, as a, as a business grows larger, it's harder to be able to tell the stories directly with, with, with everyone, and so it's just a great Opportunity to encapsulate all that and, uh, share, you know, what happened really, the good and the bad, the, Things that worked well. Things that didn't work well. And, um, you know, I certainly benefited from reading the stories or hearing the stories of other people and thought it'd be a good idea.

AI assessment note: “I wanted to kind of document it, and it was during COVID.”

Q You mentioned earlier that you benefited from studying people that came before you, and this is, you know, you wanted to pass that forward. Like, who are a few of the people that you study, you felt you learned from, or that influenced, like, your thinking about how you're building, how you built your business?

A You know, when I was, when I was a kid, I, I, you would read about entrepreneurs, you know, that were starting companies, Charles Schwab or Fred Smith, certainly Sam Walton, some of the early telecom pioneers, people that were doing it right then, like in the seventies. And those stories were also, were just super interesting to me. I grew up in Houston, which was kind of a boom town. You see these new companies being created, and parents were talking about that. And so, those, those stories were always just interesting and compelling, and you want to understand, well, how did they do that? Why did they do that? And, you know, what happened? And, you know, I never imagined myself doing anything else other than starting a business. You know, the idea just was in my, in my consciousness From, from a very early age.

AI assessment note: “Charles Schwab or Fred Smith, certainly Sam Walton, some of the early telecom pioneers”

Q What was your hypothesis back then? Do you remember?

A Oh, it's pretty simple. It's that it will be possible to dramatically improve the way we do things in all the core processes of the business, from software development to support to sales to every major function, our supply chain. Everything can be improved in a dramatic way. That's what we're doing, and we're finding, you know, as we take our data, as we reimagine the processes and simplify and standardize them, we can make them way more effective. You know, example would be, uh, in support, we have incredible amounts of data. We have telemetry data that the machines are giving us all the time, right, about, uh, you know, soft errors and all these things that are going on, you know, inside the usage patterns from customers. We have warranty data. Uh, you know, we have previous call logs. We have all these knowledge bases. We have JIRA databases. It's like millions and millions of documents. No human could ever interpret all this, and so we created this tool called Next Best Action, which takes all this data and understands what problem the customer's trying to solve, and it helps, uh, either the customer or the agent that's trying to help the customer get to exactly the Best way to solve that problem in the fewest possible steps. And so the person helping them feels like, wow, I'm way better at my job than I used to be, because now I got this genius on my shoulders telling me …

AI assessment note: “It's that it will be possible to dramatically improve the way we do things”

Q So, we were just talking about the fact that Compact and IBM, they were almost like Essentially, you got fuel from being underestimated. You've mentioned in the book that, like, you found it, I think you said something that's like a powerful motivating force. Do you recall why you felt that way?

A Yeah, it was, it was just, it was just like, okay, wow, this is going to be a multiplier for us because they underestimate us. They don't understand what we're doing. And, and so, uh, they, they didn't see us coming because they were underestimating us, you know. I think, ah, the CEO of Compaq, you know, would, would refer to us as a mail order company, or, you know, garage operation, or whatever, you know, and you'd hear that, and you'd go, oh, wow, this is, this is great, right? It's like, they have no idea what we're doing. All, all that was motivating, you know, any time You know, there, there was sort of a, a setback and the conventional wisdom or even whatever interpretation was, okay, you know, they're going to fail, they're going to go out of business, all that incredibly motivating.

AI assessment note: “this is going to be a multiplier for us because they underestimate us”

Q And he's like, all right, now we're coming with Osborne two, it's even new and improved and it's great. And you make the point, it's just like, Yeah, maybe, but it didn't ship in time, and so now you just made this big announcement where, like, we have this great new product. It's even better than one. What are you telling to the market?

A The Osborne effect. I don't think people talk about it so much anymore, but back then, the Osborne effect was a thing where you introduce a new product that's better than your first product, and nobody buys your first product anymore, and you're, you're out of business. And so, you know, yeah, don't want to do that. So, so, Go make some mistakes nobody's ever made before. Try to make them in small increments. Fix your mistakes as fast as you find them, and you actually want to make mistakes. You just want to make them small and, you know, iterate and fix them quickly. I mean, one of the things when you're, when you're creating a new business in an area that has never been done, or with some new technology, new business model, there's no playbook. There's no, like, book you can read. So here's how you do it, right? And, and if you hire the people from the adjacent, you know, industry companies And ask them to go do it. Well, they're just going to go do what they were doing before, right? And so that's not going to work. So you need a lot of creativity, and you need to sort of intuit your way to the answer by experimenting. It's like, okay, uh, here's a theory that we think will work. Let's try it, right? And, and, and, and, you know, does it work?

AI assessment note: “nobody buys your first product anymore, and you're, you're out of business.”