Ep 395 | Profits are Made Through Expense Management

Thank you for joining me today. It's Brian Gubernick, and welcome to the No Days Off podcast, where we believe that every single day brings a new opportunity to get better. Today we're going to do something a little different. At least I don't think we've done this before. If we have, it was unintentional. Today we're actually going to revisit a past episode because I think that this particular concept has evolved since we first talked about it. I want to bring you all the way back to episode 180. So, a couple hundred episodes ago. Can't believe we've done that many already, but we have. In that episode, episode 180, we talked about this concept of firing bullets before cannonballs. Now, just to recap, Though I encourage you to go back and listen to it, you'll get a more detailed explanation of bullets before cannonballs. But Jim Collins, the author of several great books, including Good to Great as well as Great by Choice, had this metaphor called, you know, where he said fire bullets before cannonballs. And what he was really talking about was testing ideas with smaller, low-risk experiments. I.e., the bullets, before you commit significant resources to a larger, bolder initiative, which would in this case be the cannonballs. So if the small test is successful, then you have some degree of confidence when you scale up. And what happens here is the strategy helps you to minimize risk and conserve resources, conserve money, and increase the likelihood of success when you end up making the bigger investments or taking on larger projects down the road. So leveraging this firing bullets before cannonballs mindset leads to this more disciplined or iterative, iterative, iterative approach to decision-making and to, to innovation. In the, in the book, if you go back to it, he really uses like two ships in his analogy, and he says, you know, imagine you have a limited amount of gunpowder and one ship is is trying to shoot at the other. Now, if you pack all of your gunpowder into a cannonball and you shoot that cannonball, but you miss, you're all out of, you're all out of gunpowder, you're all out of ammunition. Instead, what Jim would advise is to load, say, a small bullet and shoot that bullet. And let's say you miss and you're off by, you know, 80%. Well, now you adjust the trajectory and then you shoot another bullet. And now you're off by 40%. You shoot another bullet and now you're off by 10%. And then you shoot another bullet and you hit. Now you take the remaining gunpowder, make the cannonball and shoot. And sure, that cannonball will not be as big as the very first one you shot, but it will make contact. It will hit and will likely create some degree of success. So the idea again is one about experimenting with small-scale tests before you commit significant resources. Now, why am I talking about this? At this very moment, I am very, very intrigued and trying to learn as much as possible about AI, about this artificial intelligence movement. Now, this has been going on for a while. Uh, we've all seen it. We've seen these things develop what feels like rather quickly, and it really has hit this geometric progression. And I am looking at it quite often because I think that our world is going to look dramatically different, business and personal, in not years but potentially months. I think lots of things are going to change, and I would like to do all I can to better understand how AI is impacting me today and is going to you know, potentially impact me in the future. So historically, when we've tried to demonstrate bullets versus cannonballs or before cannonballs, you know, I think in episode 180, we had turned to Apple and described how Apple, you know, the bullet— they shot a bullet with the iPod and they shot a bullet with iTunes. And when they saw these things hit, they combined them and they shifted from, you know, a computer-based company to that of the iPod that evolved into the phone. And so that was a great example. And I think we maybe used Amazon in this example, and these are still excellent examples, but I think we ought to start looking at what's going on in the AI world. Let's take OpenAI, who you may know of, or at the very least you probably heard of ChatGPT, which is OpenAI's model. OpenAI released a very small model called GPT-2, and it scaled after seeing that it was working While that GPT-2 had the knowledge of, you know, basically a kindergartner or maybe elementary school kid, as it developed, it then scaled to larger versions like GPT-3, then GPT-4. And this has allowed them to gather more data on use cases and risks and improvements before they continue to invest more heavily, I would say, in more powerful models. Now, OpenAI is super intriguing to me. Why? Well, because just recently, you know, here we are in September, October of 2024. OpenAI just recently announced that they're going through the process of converting from a nonprofit to an actual C corporation. So they went from nonprofit to for-profit. This is happening right now because they perceive that there is massive revenue opportunity. In other words, They've shot enough bullets to go now drop the cannonball, shoot the cannonball. How about Waymo? Now, I am in Phoenix, and so I see Waymo all over the place. Many of you may not even know what I'm talking about, but Waymo is autonomous, an autonomous, you know, car that operates like Uber. So in other words, you get picked up in this autonomous driving car, no driver in the seat, and it operates just like Uber. I'm taking Waymo now all the time. Waymo, however, is operating in only a few spots, Phoenix being one of the very first. This is the bullet. This is the bullet being shot. Because Phoenix, if you've been here or you've spent some time here, the, the, the map of Phoenix, the streets of Phoenix very much are grid-like. In other words, things go north, south, east, west. And so Waymo can operate more effectively and efficiently in a city like this. It's not as, you know, it doesn't have the turns and, and like the older school, uh, East Coast cities, things of that nature. It's a lot easier not just for it to operate but for it to gather data. Waymo also presently, for the most part, stays off the freeway, not necessarily because of the risk, but according to their CEO, who I had the opportunity to speak just a few weeks ago, she had explained it's not so much the safety— we're good on safety It's our ability to gather data. In other words, we cannot gather as much data driving 65 miles an hour, 65 miles an hour on a freeway where there's not a lot happening from like an information gathering standpoint versus driving through intersections and busy city streets. So right now in Phoenix, Waymo gathering more detail by using city streets. Again, shooting a bullet. Staying in Phoenix, geofencing around a specific Phoenix area, using only streets. This is a company that is just simply shooting bullets before the cannonball that is what probably multiple markets. Tesla's AI, specifically for autonomous driving. Tesla began testing its self-driving technology with very, very small features like Autopilot, or I think it has, uh, Summon is what it was called. And that they did that before gradually expanding the full self-driving capabilities. These were incremental rollouts that let them refine the technology and improve safety. And ultimately, Tesla will have a vehicle where there won't be a need for a driver to be sitting in that seat. You will own one. So I, I want to, you know, I'm revisiting this concept because obviously things are evolving real time in our world, and I want you to be educated around them. But I also want to ask you, like I did in episode 180, Now, a couple hundred episodes later, how are you leveraging this bullets before cannonball process in your own business or in your own world? Are you firing little bullets to test different theories, different products, different services, prove that they in fact have an upside, and then drop or build the cannonball? See, what I see happen all that often all too often in business is there's not enough testing and iteration, shooting and then adjusting trajectory, shooting again and then adjusting trajectory. Instead, what I see is someone try to hit a grand slam right out the gate. And while every once in a while it hits, and that's usually the ones you hear about, 98% of the time it does not. And those are the businesses, the companies, the individuals that fade. So how could you leverage this bullets before cannonballs concept in your business world today, where you put a toe in the water, test, test, test, iterate, test again, and then launch? Where does this apply, and how could you leverage this concept better so that you have even greater success? That's what I'd focus on today. That's all I have for you today, the No Days Off Podcast. Thank you so much for listening, and remember, every single day brings a new opportunity to get better. So let's get after it.