00:21:03 · Luca Ferrari
So we have made it a science really, an it's entirely different discussion. If you want, we can get into it, but we have invested heavily over time to develop the tools to predict futures behavior in people who apply. Once you have the people, hopefully you have a lot of people that are predisposed toward behaving like owners, it becomes very important to maximize their potential in that regard. Part of the problem is solved by creating a high density of people with this sort of high levels of care because caring is contagious, but also negatively contagious. If almost everybody cares, the one person who cares slightly, if they have the potential to care, the poorly care. Vice versa, if almost nobody cares, all those who are in the middle line could care or not care end up not caring. You want to have a very high level of gravitational pull toward the caring pull. And so hiring well, and that's part of it. Then you try to retain accordingly. So if someone doesn't care, want to part ways with them. You want to preach constantly. This is important. First and foremost, you as an individual, especially if you're in a position of greater visibility, you need to embody that quality, no matter what. So every time you get a chance to demonstrate, in our case, extreme ownership, if you don't, especially as a manager, as a leader, that's your greatest failure. I'd rather have someone make a bad decision, but consistently demonstrate Extreme Ownership than vice versa. Because when people see that people who progress in the organization get more responsibility and better pay, the one trait everybody has is that they care tremendously. If you have the potential to care, that will be very powerful in maximizing that potential. It's never going be perfect, but if you do all these things well, over time, you'll be at 80 out of 100, where most companies are 20 out of 100. Ultimately in life, almost everything is relative. Nothing is perfect. You just want to win, relatively speaking. It's almost like basketball. Nobody shoots the three perfectly, but if you shoot at 45% on average, your team and most other teams are at 38, you're very likely to win vast majority of matches. So you shoot for the highest possible average, not 100%, which is impossible. It's so fascinating how you're talking about the individual unit of a Spooner of a teammate.
00:23:09 · Luca Ferrari, Paul Buser
When you go from five of you to 50 to 500 eventually to 5,000 or maybe not, I don't [00:23:13] S1: know where it goes, how do you keep a grip on the organization? Feels like actually what you described could be one answer that if every individual unit, individual person feels ownership, you could have an unlimited amount if you actually could do that. But the history of corporations and law of large numbers tends to fight against that on average. As you grow the team, what sort of management system do you use to either keep control of that, maybe diffuse it, stay centralized, I'm
00:23:45 · Luca Ferrari
[00:23:45] S3: more worried about our ability to find enough great people, but not so much about the scalability of the model per se. I think what we find consistently is that the best antidote to handle, let's say, complexity and scale is the combination of talent density and extreme ownership that beats rules, processes, centralization of decision making any day. I've heard people say that Bending Spoons is highly centralized and that's completely true or completely false, depending on how you define it. Centralization is a broad concept and the devil is in the details. If we talk about decision making, for example, we're extremely decentralized. At any point in time, each of our businesses is run, but also our platform teams are run by a dedicated team of Spooners and acquired team members, if it's a business. At any point in time, they have a complete mandate to do whatever is needed to help not that business, but Bending Spoons as a whole succeed, which generally is started by running that business well. I and others monitor, oversee progress by being immersed in all the different Slack channels and threads, and looking at dashboards and analysis. But no decision has to go through us to be, let's say, call it the executive team, whatever that means, to be approved other than a super small set of decisions, for example, related to pricing. But we're talking maybe decisions that are made once a year, 99% decisions. The teams are trusted to take them. We sometimes joke that we buy established companies and we bring them back to startup mode. And we really do. These small talent dense teams with massive mandates to just go and get it. So decision making is extremely decentralized. And I don't think we'd be able to scale otherwise, because centralized decision making has multiple flaws. Obviously it can be slower because you don't have time and people have to wait. You may not have enough context to decide well. And especially if you have an inflated sense of ego, then you're probably still going to think that you can make up for that lack of context out of your extraordinary intellectual abilities. But then guess what? Often you don't. But the most important flaw of centralized decision making is that it deprives people of that precious sense of ownership.
00:25:51 · Luca Ferrari
It's difficult to feel excited about the work and responsible for the work if ultimately all the important decisions someone else has to place a stamp of approval or even make them then destroys productivity on a daily basis. So we don't do that. Another way people define centralization is rules. So very specific rules for how things are done. And I think that's partly a way that management teams try to implement their decisions at scale. They believe they know best, they decide, and then rules are the way that those decisions are imposed throughout the... Rules become a bureaucracy, obviously could be more or less complex and more or less red tape, but sometimes rules are just an enabler for centralization, meaning if you strongly standardize how people operate and report, then you make it more feasible for this supposed central management team to make their decisions. If they had heterogeneous information, it would be more difficult. We don't do that either. We actually tell our teams, don't report in a way that makes me happy. Use Slack channels to talk to the team. I'll use the same info for the most part. If the info is bad, it's because it's bad for everybody. I'll tell you, but not because it's bad because I don't like it structured that way for the most part. What we massively, let's say, centralize, I don't know if centralization is the right word, is we standardize the toolkit. The underlying technological foundation is the same for everybody, but that's something we bring in on almost on day one after a new acquisition takes a few months and then it's done. And by the way, businesses still have control. We are like an open source community internally. So if you find that there is a bug or a missing feature, you build it and that benefits all the other businesses. So it's not that you're limited necessarily. And then we give you a set of principles, good ideas and lessons learned that hopefully you follow, but they're not prescriptive. They're not rules. We have a massive homogeneity. We make sure that the toolkit and the principles are homogenous across the group. But then operationally, in terms of decision making on a daily basis, teams are completely autonomous. And for us, that's worked pretty well so far.
00:27:55 · Paul Buser
[00:27:55] S1: How has the chatty pity moment influenced that? I know I have heard you say that you were doing AI back thirteen years ago when you launched this, even your previous company. Now these tools have become much more useful at scale. How does that figure into this equation of centralized versus decentralized and ownership by people?
00:28:14 · Luca Ferrari
[00:28:14] S3: AI is having a massive impact on productivity for us. It's enabling people to do more, faster, better work. It helps in the context of scalability. I think it helps in a bunch of ways. Again, if each person can do more work, you need fewer people to say, absorb the same number of companies or larger companies, which in turn makes a lot of challenges easier. For example, you don't need to hire as many amazing people or people capable of extreme ownership, which is a win check. Alternatively, you could do more acquisitions in parallel or bigger acquisitions, which is good for growth. It also helps keep the organization functional at scale because it makes producing documentation much faster. Now writing a memo describing, say an experiment becomes 10 times faster than before potentially. We're trying to automate it fully, by the way, it's mostly automated already at Banish Spoons. Similarly, if I need to follow progress across different businesses, I need other people less. I can be more autonomous. In the past, I had to ask to be granted access to the relevant database. I would need to query data or ask a data scientist to query for me, have them run an analysis, do it myself. Now I go on Slack, we have built a set of technologies and automations, the superficial layer of which we call alternative spooner. And I've got my own Alternative Spooner, I will ask it to run that analysis and then it will go and automatically request access to the relevant database. Access will be automatically granted for say five minutes, the amount of time that the agent needs to review the data. It will compile the analysis, it will share it with me whether it's a plot or in textual form. And so I can be autonomous and even though I don't have time to follow everything in detail, I can very quickly catch up indirectly through the agent. So it is a boon. It makes us even more bullish that a call it centralized model, I think it could be a slightly misleading word can scale massively much more so than what would have been possible in a more traditional, technologically speaking, side of boundary conditions.