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The Algorithm for Hypergrowth with Jon McNeill, CEO at DVx Ventures & Former President at Tesla

Richie and Jon explore the algorithm behind Tesla's 10X hypergrowth, why automation should always come last, how to find and delete unnecessary process steps, changing the currency of promotion, running effective meetings, and much more.
14 sep 2026  · 38 min lezen

Jon McNeill's photo
Guest
Jon McNeill
LinkedIn

Jon McNeill is CEO and co-founder of DVx Ventures, a venture studio that has launched 12 companies. He previously served as President at Tesla, where revenue grew from $2B to $20B in 30 months, and as COO at Lyft through its IPO. A serial entrepreneur, he's founded and sold six companies, sits on the boards of Lululemon and Asurion, and wrote The Algorithm: The Hypergrowth Formula that Transformed Tesla, Lululemon, General Motors and SpaceX.


Richie Cotton's photo
Host
Richie Cotton

Richie helps individuals and organizations get better at using data and AI. He's been a data scientist since before it was called data science, and has written two books and created many DataCamp courses on the subject. He is a host of the DataFramed podcast, and runs DataCamp's webinar program.

Chat with AI Richie about every episode of DataFramed - all data champs welcome!

Key Quotes

This may surprise you coming from Silicon Valley, but our rule is we automate last. It's the last step in the process, and that's because we've been burned too many times by automating first and then having to go back and redo everything we've automated because we didn't really think through the process the first time, and we didn't optimize it. Our rule in the algorithm is automate last.

One of the secrets to organizational design that makes this work is small teams. I think we're seeing a shift in organizational design theory — it started when people realized Jensen Huang runs NVIDIA, the world's most valuable company, with roughly 65 small teams that report directly to him. These are small teams with specific assignments that aren't tied down by budget or roadmap, and they report directly to the CEO on a very specific objective.

Key Takeaways

1

Automate last, not first. Simplify a process and run it manually until it's smooth before adding any automation — automating a broken or unnecessary process just locks in the waste.

2

Force every meeting to answer three questions before it happens: what problem are we solving, do we actually need a meeting to solve it, and who has the authority to decide.

3

Map your process against what customers actually pay for. Anything a customer isn't paying for — sign-offs, change orders, extra paperwork — is a strong candidate to delete entirely rather than optimize.

Links From The Show

The Algorithm: The Hypergrowth Formula that Transformed Tesla, Lululemon, General Motors and SpaceX by Jon McNeill External Link

Transcript

Richie Cotton: Hi, Jon. Welcome to the show.

Jon McNeill: Hey, thanks for having me.

Richie Cotton: Yeah, great to have you here. So we're gonna be talking about your algorithm for hypergrowth today. Before we get into the details, do you wanna tell me what's your favorite success story from using this algorithm? 

Jon McNeill: Oh, gosh. I think maybe the favorite success story is the story that yielded this whole model.

And that is growing from roughly $1.8 billion in revenue to $20 billion in revenue in 30 months at Tesla. So 10X-ing a company at scale in 30 months. Okay. Yeah, 10X-ing that's the dream. And yeah, who wouldn't want $20 billion? That's that's some amazing stuff. All right do you wanna talk me through just give me a high-level overview of what this algorithm is, and then we can figure out the details.

So it's basically a framework that we developed over time at Tesla to help the organization drive innovation at every level of the org, which we needed to do. If you're gonna 10X a business in 30 months, you've got to have a framework that not only leadership's following, but everybody can follow. And so that's what this is.

This is not meant for incremental growth. It's meant to drive quantum growth and drive big breakthroughs in innovation. 

Richie Cotton: Okay. That sounds amazing breakthrough in innovation, something like for the whole company. Now I know one of the steps in this algorithm is all about automation. That... See more

's been, of course, like the big story of the year has been like, can I automate everything with AI?

Do you wanna talk me through, like, where is automation appropriate? How do you make use of it within the context of this algorithm? 

Jon McNeill: So this may surprise you coming from Silicon Valley, but our rule is we automate last. It's the last step in the process and that's because we've been burned too many times by automating first and then having to go back and redo everything we've automated 'cause we didn't really think through the process the first time, and we didn't optimize it.

And so our rule in the algorithm is automate last. 

Richie Cotton: Okay. I think that might surprise a lot of people or at least go against the instincts of a lot of people who are working in tech where you're like, "Okay, that's the whole point of technology, right? You can just automate everything straight away, and then you don't have to do stuff."

I can certainly see how you can get burned by doing that too quickly. What do you do before then? Talk me through the previous steps. 

Jon McNeill: So basically you gotta super simplify your business approach and then optimize. The first step in the algorithm is question every requirement, because that's the most simple you can get, is if there's no requirement, you don't have to do something.

And if you don't have to do something, that goes fast and smooth every time. So the first step is eliminate and question every requirement possible. The second step is once you've done that, then you simplify further. You delete every step essentially that the customer's not paying you for. The third thing you do is then you start to run that process manually, and you start to work out the kinks.

Fourth thing you do is apply speed to that process 'cause that shows where all the quality flaws are. And then once you've got a super simple process that operates at speed, now automate. 

Richie Cotton: Okay. I love that, and I particularly like the first two steps are about not doing work. As much as I love my job, I also like not doing things as well.

Maybe do you have some concrete examples of this? Let's start with the thinking about the process and what you can get rid of. 

Jon McNeill: I'll give you an example that comes from Elon himself. When we were bringing out the Model 3, we were having a terrible time trying to manufacture one part, and the part was a separator between the battery and the passenger compartment.

And it's basically, think of it about as a thick sheet of plastic that's gotta go the full length of the battery. And we were having all kinds of problems with that thing. It would warp, it would delaminate and we could not get it right. And we were dividing and conquering, and so Elon took that challenge on.

He went right to the factory where this was being built, in the cell it was being built, and spent three weeks trying to figure out how to manufacture this thing so it wouldn't come out warped or delaminated. And they were making a little progress, but not much. And finally one night, he broke down and asked the team, "Who spec'd this part?

I wanna talk to them." And he happened to be standing next to the battery team, and so they said Oh, this wasn't us. This is the ride dynamics team. Ride dynamics is like the soundproofing of the car, the smoothness of the ride, that sort of thing. So he goes to the ride dynamics team and says, "Why did you spec this separator between the battery and the passenger compartment?"

They said, "We didn't." He said, "What are you talking about we didn't? The battery guys told me you specced it because of noise." And they said, "No, we didn't spec it. The battery guys specced it because of heat. They wanted a heat shield between the battery and the car." He said, "I was just talking to those guys.

They said they didn't spec it. Give me the name of the person who specced it." So they go in the system and they look up the name in the engineering design files, and the name of the person is a summer intern that didn't work there anymore. So he looks up and says, "I just spent three weeks of my life trying to optimize a part, trying to automate the manufacturing for a part that didn't need to exist."

So that in reverse order is how the algorithm works And so what you do is, at the very beginning of that process, you ask, "Who spec'd the requirement for this part? Is it necessary?" The answer would've been no. Okay, now we can go to step two. Let's delete it. If we delete it, now we don't have to automate anything.

We just-- The process is gonna run faster and smoother without it. And that's an example of how the algorithm now works in practice, and also an example of, like, where it came from. It came from these mistakes that we made where we asked ourselves, like, "How do we not do this again? How do we not let a summer intern s- spec a part that ends up driving us crazy and slowing down a, an important model launch for us on a part that didn't even need to exist?"

So that's the c- core and heart of what the algorithm does. 

Richie Cotton: That's an amazing cautionary tale of Elon Musk wasting three weeks of his life on something a, a summer intern did. I guess more generally, do you have a sense of, like, how you find all these stupidities that have, that exist in every business?

There's gotta be tons of things that every business can get rid of, but how do you find them? 

Jon McNeill: You start by looking really at the, first at the financial physics of the business, the P&L. And you look at, okay, where are my biggest levers in a P&L to improve the business? And your financials can basically guide you to the location or the postal code of where you need to work, and then you can start to apply the algorithm.

So it's not like you're gonna apply this every day against every situation. You wanna apply it where you get the most leverage. And in every business, there are three or four major levers that you can pull to make that business a lot better. So you go looking in those areas, and then you start to hone in and re- and start to then question requirements.

Like, why does this exist? Who said it should exist? Do laws of physics say it should exist? Does the law of safety or regulation say it sh- should exist? If the answer to those questions are no, now you've, you're on your way 'cause you've now started to eliminate stuff that didn't need to be there in the first place.

Richie Cotton: Absolutely. I love that. Certainly starting with what's gonna have the highest leverage on your business, and that's the place to look for can I simplify stuff? And then maybe if it's a s- if it's small fry, you can, that can wait till later. The second tip is about deleting things, and I feel like this is gonna be the scary part for a lot of people, 'cause what happens if you get rid of stuff that later turns out to be useful?

Like, how do you know what you can safely delete? 

Jon McNeill: You shouldn't be fearful of deleting especially if you can go back and and put that step back in or turn it back on. But the whole point of deleting is a lot-- In every business I've seen, processes and steps and rules and procedures grow over time, and nobody really stops and goes back and questions, "Do we need to do this?

Why are we doing this?" Et cetera. So a really valuable exercise for teams is to map out a process and then circle all of the process steps that a customer actually pays you for. And you'll find out that customers don't pay us for engineering okays. They don't pay us for change orders. They don't pay us for purchase orders.

They don't pay us for accounting. They don't pay for a lot of stuff. What they pay for is to get their product And when you took-- when you take an eye at a process and say, "All right, we're gonna try to eliminate everything the customer doesn't pay us for," real creativity starts to come out. 'Cause you say how would I do this if I didn't have a purchase order?"

There is... Turns out there's a way to do that if you really think through it, and that eliminates a whole overhead cost that customers aren't paying you for to begin with. So it's maybe one of the most useful steps in this process, is to go through that exercise, figure out what the customer pays you for, and then try to delete everything they don't pay you for.

Richie Cotton: That's wild. Yeah. I guess everyone knows that businesses have cost centers, but you don't necessarily think about okay, how is what I'm doing directly tied to something the, the customer is gonna pay me for?" Okay. So you mentioned mapping processes, and with your earlier story, you talk about it was the battery team thought the ride dynamics team wanted something, and the ride dynamics team thought the battery team wanted something.

It seems like cross-team communication's often the hard bit, 'cause it's the people you're not sure what they're doing. So if you're deleting stuff, what happens when you wanna delete other teams' bits of work? 

Jon McNeill: That means that a member of each team probably ought to be on that process change or the algorithm team, let's just call it.

Because you want everybody around the table to be able to cover the entire process and to be able to decide, 'cause decisiveness is key in this model. So it's really defeating when a team has to stop and say we gotta go check with somebody else to see if we can do this." It's good to have that somebody else in the room.

Richie Cotton: Absolutely. Yeah, but once you start interfering with other people's processes, you need to chat to that, those, that that person before you start messing with their work. Okay. So I guess... Is there also, is there a proactive way of doing this by not introducing overly complicated processes in the first place?

Like, when you're designing processes from scratch or to begin with, like, how do you keep them simple and not end up with the bureaucracy and overly complicated lifestyle? 

Jon McNeill: I think when you're inventing from scratch, you apply these same things. And so an example of that is we were starting to sell cars online, which really hadn't been done at scale ever, because people tend to wanna test drive a car and see it and sit in it.

It's a major purchase. Most households, it's the second largest purchase they'll ever make outside of their actual house. But we decided to try this, and so we questioned the requirements of every step in the process. Do we really need to offer an, an infinite configuration of colors, of seat materials, of motors?

And what we did was we questioned the basic business model of of the company at the time, which was build to order and custom. Instead, we offered kind of two or three options online, versions of the car. And then we asked ourselves the question, like, why would we put a customer through a 12-page loan or lease document for the car?

So we went to the, to our lead corporate attorney and said, "How many of these 12 pages are the requirement of law or regulation?" And they came back and said, "None." And I said, "What do you mean none?" And they said the case law is already established. If you don't pay us for the car, we can go take it back.

That's established in case law. We don't need 12 pages to say that." And we've got 12 pages here of paragraph after paragraph that was developed by well-meaning attorneys to protect their company. But at the end of the day, we don't need them So we started a process from scratch of selling cars online where you could have a one-click loan or lease.

And so it deleted an enormous amount of steps that we didn't have to automate, didn't have to run the customer through. Customer wasn't paying us for those 12 pages. And and today, Tesla is the world largest seller of cars digitally online. It was a whole process that was-- that really came from invention and applying the algorithm along the way.

Richie Cotton: That's cool 'cause you think about car innovations being like mostly an engineering thing, but actually this is a case of like just making a buying process easier. And I think apart from, maybe apart from the lawyers, like no one's gonna be like too sad if you don't have to fill in paperwork on that 

Jon McNeill: kind of thing.

Yeah, exactly. Exactly right. 

Richie Cotton: Yeah. W-we talked a bit about how you go about creating processes. I guess there's also like a, a cultural aspect to this. How do you set up like a, a culture where it's possible to devise good processes and how do you go about implementing the algorithm in practice?

Jon McNeill: I think setting up the culture has a few key ingredients. Yeah, and it's typically a culture of curiosity, curious people who aren't satisfied with the status quo. It's a culture of people who like to win 'cause they're gonna defeat their competition. It's a culture of humility in the sense that we have no idea how to do this, but we're gonna set a very big goal and go after trying to solve it ourselves, and we're gonna use this process of discovery, the algorithm, to do it.

It also has to be a culture where it's okay to make a mistake. And so we talked about, often about creating a culture where there was there were one-way doors and two-way doors in terms of decisions. A one-way door is a decision you make that once you make it, you cannot reverse it. In other words, you walk through the door closes and locks behind you.

We said if you're making a decision like that, you need to talk to leadership 'cause we need to be involved. But if it's a two-way door, in other words, you make a decision, and if it doesn't work, you can go back. So it's like going through a door, you try it, doesn't work, you go back to the status quo, rethink it again, go back through the to the new solution, try it again.

If it doesn't work, go back through the door. We said to our teams, two-way doors are completely fine for you. You have full agency to make those decisions and so if you've got a culture that's curious, not satisfied with status quo, likes to win, is humble, and has agency because you've given them a framework for decisions that they can make, you can unleash an entire workforce to make the place better.

Richie Cotton: Okay. I love that idea of just empowering individual workers to be able to make their own decisions without having to go through this extensive chain of command where you ask your boss asks their boss, and so on and things go a lot slower. So I can certainly how that speeds th- see how that speeds things up.

And generally it seems like urgency is a, a big trait here. Do you have any more tips on how we can go faster? 

Jon McNeill: When academics study Elon a couple decades from now and they ask the question, how is this person so uniquely effective as an industrialist? He didn't start one company, he didn't start two companies.

He started multiple companies. You could, depending on how you count, five or seven that are worth more than $50 billion. And I think the ans- the academics are gonna come up with is he created urgency on a weekly basis in his companies. And the way that urgency gets created is not by grandstanding or yelling, it's really by process.

And so what Elon does is he creates a list of two or three things that are absolutely existential to the company, and he only works on those two or three things. And by working on them, it means he assigns teams to those two or three things, and he meets with those teams every week. So you can imagine the CEO shows up, the team that is meeting with him every week is not going to bring their B game, they're gonna bring their A game, which is really important The second thing is he's expecting forward progress, little chunks at a time, 'cause he knows those compound and build on each other.

And so when you turn around and look six or 12 months later, you might have accomplished a breakthrough a little tiny bit at a time. As a CEO driving that weekly cadence of a company against two or three objectives, there's ultimate clarity about what needs to be true and and worked on, and there is a weekly heartbeat to the company that moves the company forward.

And so examples of things that we've invented in the automotive industry using this technique are mobile service, where you can get your car serviced anywhere, castings instead of welding chassis, we actually pour them in a mold, one-click loan and lease. These things were developed over time over the course of typically less than a year, and they on average have an eight to 10-year life before the competition even tries to replicate them.

So you've built a very large competitive advantage that's compounding over time. 

Richie Cotton: I love that idea of just having a clear goal and then tracking progress on a sort of weekly basis. I'm curious what happens when you don't make progress. I'm, I was thinking okay even at Tesla I remember going back in what the mid sort of 2010s were like moments of like the, the automations didn't work and there were a few moments of chaos intermittently that I read in the news.

So yeah, what happens when you have a, a bad week or a few bad weeks in that case? 

Jon McNeill: I think the team keeps redoubling down at different methods and different vectors upon which to solve that problem. 'Cause oftentimes these problems are super hard, and you could see like in autonomous driving, you wouldn't wanna give up on the team in the first few weeks of not being able to get that done, 'cause it turns out there is a whole lot to autonomous driving that we didn't appreciate when we started in 2014, and it's now 2026 and it's just barely rolling out.

That team meets, is met every week for 12 years to get to the point that they're at, and they, there are some weeks they've made progress and some weeks they haven't made progress. But overall, they have made enormous progress Go try to drive a Toyota from point to point without putting your hands on the wheel.

You can't. Try it in a Honda. You can't. Try it in a BMW. You can't. Try it in a Volkswagen. You can't. You can't in a Mercedes. So it turns out that Tesla has a huge advantage versus their competition when it comes to this, which is why the Model Y is probably still the number one selling car in the world is because it's got this, this capability that has just been developed chunk by chunk, bit by bit over the course of 12 years, and it's now created an enormous competitive advantage.

Richie Cotton: This is a kind of marathon runner mentality in terms of p- just persevering and, okay, you have a bad week you carry on. 

Jon McNeill: But to the heart of your question, if you're not producing on those weeklies, and it becomes pretty obvious the problem may be the person, not the problem, yeah, that person's replaced.

Richie Cotton: Okay. Yeah. So yeah, th- things go wrong, like being able to just swap out your workers for the people who do get it, it is one of those tough management decisions, that, that has to be made. Okay I guess related to this, are there any other effects of like organizational structure or culture or organizational design that affect your ability to execute?

Jon McNeill: One of the secrets to organizational design that makes this work is small teams, and I think we're seeing right before our eyes a shift in organizational design theory. I think it started when people started to understand that Jensen Huang has a very different way of running NVIDIA, the world's most valuable company, where he's got roughly 65 small teams that report directly to him.

And in each of his businesses, Elon has Call it two or three teams that report directly to him. So he may have close to 15 or 20 teams that are reporting directly to him. These are small teams with specific assignments that are not tied down by the budget or by the roadmap, and they report directly to the CEO on a very specific objective.

And that's absolutely necessary to making this fast progress work. And it is it-- I think over the course of the coming years is gonna change organizational design theory from silos in very large teams to small, very adept teams that aren't burdened by bureaucracy or budget. 

Richie Cotton: Yeah. I would say, I've, I would say the, the case of Jensen Huang is completely crazy, the fact that he's s- supposedly line managing 60 people

It's like I feel like once most people get past 10 in-- people they're line managing that's plenty for them. Yeah, that seems crazy. But this idea of small teams is interesting, although I guess does it make cross-team communication more of a challenge then if you've got all these independent teams?

Like, how do you manage all that then? 

Jon McNeill: You've gotta, you've gotta communicate a lot. And so the team leaders, so let's say that Elon's got a team he's meeting with weekly there's some of my people on that team. I'm often sitting in on those meetings so I can help them clear the way in our team. And so the team, the leaders of that business sit in on these sessions every week so that they can help with both communication and with resource allocation, essentially clear the decks for the team.

Richie Cotton: Okay, yeah. So I like the idea that's the role of the manager is clearing the deck and make, making sure that pe- everyone else can get on with their jobs. We talked a lot about sort of workplace culture, but I'm curious as to how do you go about changing your existing culture?

So if you're not starting from a place where all these things you mentioned, like the small teams, the, the urgency managers clearing the path for people, how do you go about changing your culture to implement all this, to implement the algorithm? 

Jon McNeill: I think you start with what is the currency here?

And usually the currency is I wanna be promoted, and and so the currency to get promoted is not making a mistake And that's, that is the currency in a lot of corp- corporate environments. And so changing the culture, I think, starts with changing the currency, which is currency here used to be, don't make a mistake.

Currency now is make an impact, and people that make impact are going to be promoted rapidly. And so we've changed the currency of promotion now from risk to risk-taking, and that's super important. It's also important to, to really articulate, here's the kind of people that we're gonna promote. They've gotta be curious, they've gotta have a bias to action, they've gotta have proven impact.

If they do those things, or people who do those things will get bigger and bigger opportunities here, bigger remits, bigger jobs. Changing the currency of promotion, I think, is the f- first fundamental baseline thing you have to do. 

Richie Cotton: Okay. I love that. Particularly people who are curious and have a bias to action being considered more important, they can have a bigger impact there.

Actually are there any more skills or traits that you think are important for individuals? What do you look for when you're hiring? 

Jon McNeill: So we look for those things. We look for, are they curious? Do they have a bias to action? Have they had impact? Do they have a followership because they're natural or or learned leaders?

And we keep it as simple as that. We want curious, action-oriented, high-impact people who people enjoy working with and wanna follow. And so that's what our hiring criteria is and seek to uncover as we go through as we go through interviews. 

Richie Cotton: Okay. That's fascinating. But d- do you also need people to follow those people 

Jon McNeill: that you're hiring all these leaders?

You want to have not only, a team just made of leaders, but a team that of doers as well. But the interesting thing in these models is everybody's a doer in the sense that even I as a leader am on that team and locking arms with that team and trying to either solve that problem or grow that portion of the business.

And so there are some cases where even as the leader, as the president of the company, I'm just a team member. I'm subordinating myself to that team. And so I'm a worker too not just a leader. And so we want people that can wear both hats, both lead and follow really effectively. 

Richie Cotton: Okay, nice. I've, I imagine that's a challenge to be to be able to master both sides of that.

But yeah it sounds like the ideal situation. 

Jon McNeill: I think if you think about it as a leader, you wanna be a, you wanna be somebody who's pr- clearing and solving big problems. And the people that have an answer to how to solve those problems or even what problems to work on- Are your frontline people.

They know exactly what's wrong with the product. They hear about it from customers all day long. They know exactly what's wrong with the company. They know they know what frustrates them. So I've found that really good leaders actually start with frontline employees and say, essentially, "Tell me how to do my job.

If you had my job for a day, what would you do?" And they'll often say the same thing "I would change this. We'd do this. Drives us all crazy, or it drives customers crazy." And as a leader starts to humbly ask the front line what would you do if you were me? You start to get real insights into what m- can make the business grow faster and more profitably.

Richie Cotton: Okay. Yeah. I love that. If you're a leader, speak to your employees who are closest to the customer and understand what the challenges are. And I guess more generally a, a lot of these things we've talked about with the algorithm, they've been very leader-focused, like about designing processes and things like that.

How can individual contributors c- contribute to this hypergrowth formula? 

Jon McNeill: So we had teams that were made up of individual contributors and leaders and junior leaders and senior leaders and and and different functions. And I think every if you looked across those teams, the contribution was from everyone on that team.

So it's hard to do this if you're just an inc- individual contributor and you start to question requirements and eliminate steps, the organization's probably gonna react to that. And so this really does start with leadership, and that's why I wrote the book to leaders. Because they, this comes, this stuff is modeled and mirrored from the top.

And if it's not if the leaders aren't on board, it doesn't get very far. 

Richie Cotton: Yeah. I can certainly see how when your boss says, "What you been doing here?" I cut some steps from the process without telling anyone." That's not gonna go down well. That's gonna get you fired. Yeah. All right.

I like the idea. This one starts with leaders and then hopefully they change the culture a bit and and things are more productive then. Actually, do you ever find that there is resistance to change when you're trying to implement the algorithm or when you're trying to- Yeah ... change the culture?

And- Yeah ... how do you deal with that? 'Cause I think 

Jon McNeill: I think humans enjoy status quo. And and we enjoy balance. And so I've found myself looking in the mirror saying, "I'm the problem" at some points 'cause I'm defending the status quo. And so I think number one, recognizing the change is uncomfortable for everybody or most everybody is critical.

And but then having right beside that understanding that change is difficult, understanding the why we are doing this is really important. And so a leader's first job is to explain why. Why are we doing this in the first place at all? What is it neces- why is it necessary?

What's it gonna create on the other side that's essential for the business? And leaders need to be really good at telling the at telling the why. 

Richie Cotton: Okay. Yeah. I get if the leaders explain what the point of things are, then usually it's a bit easier to swallow rather than just, "Go and do this without me explaining anything," 'cause yeah, you're gonna get a lot more pushback that way.

So I'm trying to think of areas where there's lots of stupid things that you could probably delete or optimize, and meetings are my number one thing. I think that most people think, "I spend too much time on this. I'm wasting time here." Do you have any tips for running effective meetings or for even for getting rid of meetings?

Jon McNeill: Sure. I think my partner who ran operations at Tesla, he's now my partner at DBX, Karim Bousta, has a great model for this. When you schedule a meeting, y- you get an immediate message from him that says, what is the purpose of this meeting and what problem are we trying to solve?" And it's a brilliant question because I find a lot of times people get in a room and they're, and are not even clear on what problem they're trying to solve So to make meetings more effective, start with that.

What problem are we trying to solve? Karim's second question is, do we really meeting-- need a meeting to solve that? And his third question is, who can decide? Who's the decider? And if you have a real problem defined that needs to have multiple people in a room to dis- to solve it, and you have a decider, then you can have a meeting.

But if you don't have those elements, don't have a meeting, 'cause meetings are largely a waste of time and a drain on our schedules. So we were very anti-meeting biased at Tesla because it is such a huge time sink, and so we developed that framework to figure out if we should even be in a room in a meeting, and we've carried that on to our firm now, where I have very few meetings on my calendar during the week.

I have a lot of conversations with people during the week, but no-- very few formal meetings with multiple people around a table. Because we're trying to make a direct line of communication, not a indirect line and we're trying to really work problems in real time and have them defined, and it turns out you don't need people in rooms to do that.

You need to go to where the problem is, and so get-- sit beside the desk of the person who's writing the code or testing the code or deploying the code or servicing the customer, et cetera. Go to where the problem lives and solve it there. 

Richie Cotton: Okay. Yeah, certainly I like the idea of having a default questioning do I actually need this meeting?

Yeah I'm sure a lot of meetings will disappear, particularly like the regular weekly cadence thing where it's like, "Oh, let's do status updates" that could've just been yeah a message. Okay. All right. Do you have any final advice for how you go about implementing the algorithm? I 

Jon McNeill: think one good thing to do is have your team read it so that everybody has a common language and a common understanding of the framework.

I found that when there's one or two members of a team that have read it, and then they try to bring it into a team that hasn't, there's a big disconnect, and the team doesn't understand why they're doing this, what the purpose is, how it's how it's working, how it's supposed to work, et cetera. So I'd say just get everybody on the same page first and then look at your P&L and determine where could we have the biggest impact if we actually did some work on an existing business process.

And then as a team, go to work there. And I would almost guarantee you're gonna have impact And when you do, it's gonna be really visible 'cause it's gonna show up in the P&L that everybody sees. So those two steps I think are super important. 

Richie Cotton: I love that your key to business success is like everyone has to read your book 

Jon McNeill: first.

Yeah. If you're gonna try it, it's like anything. If you're gonna try a method, you better understand the method. 

Richie Cotton: That's true. I have to say, I did very much enjoy your book it i- it is it is worth a read. Wonderful. All right now I always need new people to learn from, so whose work are you most excited about right now?

Jon McNeill: I am reading Eric Ries' book, Incorruptible about corporate culture one of my favorite books over the past year is "Unreasonable Hospitality" by Will Guidara. Often I find that orthogonal thoughts can really be helpful, meaning he's in the restaurant business, I'm in the software and technology business.

Turns out I learned a lot from a three-Michelin-starred restaurant approach that I could apply to my customers and my business. So I recommend that book because I think it applies in a lot of places outside of restaurants and hospitality. 

Richie Cotton: Okay. Wait what was your big tip? What w- what was the thing you learned?

Jon McNeill: In that case, be super curious about who's across the table. And so one of the things that they did at-- So Will Guidara took a restaurant that had no Michelin stars, and in a handful of years, it had three Michelin stars. One of the things they did, which is very unique at the time, but I would argue it's still very unique across almost every restaurant that I walk in, is they had a reservation list for that night, and they have an employee that goes through and looks up everybody on that list, and they look up their social media, they look up their LinkedIn, they find out who these people are.

And so by the time you walk in, you're known. And they greet you and say, "Hey, Richie, I understand that you have an unbelievable podcast with this many listeners, and you've got a really unique approach to interviewing, and you've got a unique approach to shirts. And so we have created a dessert for you tonight that is special for you.

I think you're gonna love it." How's that for a greeting? And that's the greeting you would get at Eleven Madison Park, and they would whisk you to a table and give you an experience that was based partly on who you are. And at the end of the day, people wanna be known. That is one of the tips I picked up from that was like, how easy is it for me every time I get in a call or I'm in a meeting to understand who's in the room?

And I can't tell you how many times I get a call and people have not done the simple thing of clicking on my LinkedIn to figure out what I've done and who I am and where I've been. And th- those people that have, I can tell right away they're asking relevant questions, and I'm thinking to myself they made a 60-second investment in this conversation just to find out who I was."

And I can also tell the people that didn't make the 60-second investment, and it decelerates the relationship because I'm like, "If you... Hey, if you didn't bother to find out who you were talking to in this conversation on the other side of the phone, then you're probably not very effective at your role."

And you're certainly not as effective as the person who does do that. So that was my big tip is find out. Just find out. Be curious about the people that you're interacting with. And that's me. I think a lot of business talk about trying to personalize things for their customers, but there aren't that many that actually walk the walk, so I love that idea.

Richie Cotton: And now I'm also very curious for what is my personal dessert? Yeah. Feeling hungry just at that thought. Wonderful. All right. Thank you so much for your time, John. I very much enjoyed the conversation. 

Jon McNeill: Enjoyed talking with you too, Richie.

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