The following interview is a conversation we had with Andrew Scheuermann, CEO of Arch Systems, on our podcast Category Visionaries. You can view the full episode here: $25 Million Raised to Help Organizations Unlock Factory Data to Drive Factory Improvements
Andrew Scheuermann
Thanks so much for having me, Brett. Excited to be here. Yeah.
Brett
And I should have asked the start, do you prefer to do this in English or Chinese? Because I was watching some YouTube videos of you, and I see that you’re learning Chinese.
Andrew Scheuermann
That’s funny. You’ve done your research. Yeah, english is good. I can get around in Chinese and German a bit, but, yeah, definitely. English is my language.
Brett
Nice. What prompted you to want to learn Chinese, and how’s that going so far?
Andrew Scheuermann
Oh, it’s going very well. I really love the language. What prompted me was a number of things. I live in the Bay Area. Live in Cupertino. My daughter goes to a Chinese daycare. She speaks Chinese better than I do already. But, I mean, the other thing is the market that I’m in. So I serve manufacturing, and it’s a global market all over the world. So kind of one of the things I love about our company, my job, china is huge part of manufacturing, and so we work with a lot of folks in China. And just being able to understand that culture and the people better is a huge part.
Brett
Nice. That’s so cool. I remember that video years ago when Mark Zuckerberg was learning Chinese, and just seeing him speak Chinese just hurt my brain a little bit. It was mind blowing and very cool. So that’s awesome you’re on that journey.
Andrew Scheuermann
Thank you. Yeah, I appreciate it.
Brett
Now if we can just take a step back and let’s just go with a quick high level summary of who you are and a bit more about your background. That would be awesome.
Andrew Scheuermann
Yeah. So my name is Andrew Schwarterman. My background is, I guess, in between science and business all along. I’m a dad of two awesome kids. I’m a husband of an awesome engineer, investor, entrepreneur herself. And yeah, I don’t really have too much time for Hobies, but when I do love writing, music and fencing. So those are kind of different aspects of who I am as a person. I started Arch, specifically about seven, eight years ago now. I did my PhD at Stanford and engineering. I was a builder of advanced machines, did my degrees in material science, built a world record electronics device, and I also helped build StartX, which is a top startup accelerator, kind of like a Y combinator. Maybe some of the folks are familiar with that. I joined when I was at Stanford. It was a spin out of a student group, and we got a seed investment effectively in this nonprofit educational idea from the Kaufman Foundation and started a fund with Stanford at one point that did $200 million out of the endowment.
Andrew Scheuermann
So I got kind of at the same time as I was doing my engineering education, building advanced machines, doing semiconductor electronic stuff, I was helping a whole bunch of other amazing entrepreneurs start their companies, kind of rubbing shoulders with really cool people. Evan Spiegel Founder, Snapchat, is on the staff. In the early days, DoorDash founders were in one of the programs that I led when they were just kind of starting with the idea. So that was awesome. So I was obviously bit by the bug of entrepreneurship, generally speaking, loved empowering and helping other people, and then ended up co founding Arch. Been at it for about eight years now. Absolutely love it. Combined kind of the advanced machine building, understanding machines background that I had with overall entrepreneurship and bringing a software and AI solution to market.
Brett
And would a younger version of Andrew be surprised that you’ve ended up in this position today and that you’re a Founder, an entrepreneur, and CEO, or did you always think that something like this could happen?
Andrew Scheuermann
It depends how far you go back. So, yeah, if you just go know, started my master’s degree, I was already, like, at that point, I was like, that’s where I want to be. But if you go to my bachelor’s degree, much less if you go back to high school, middle school, I never thought about anything like this. I grew up with a Navy and then a space program dad, so we kind of moved all over to the different space programs. I lived in Seattle. I was born in Seattle, but I grew up mainly in Alabama, Texas, and Florida at the different space centers or launch pad sites. And there weren’t necessarily that many entrepreneurs or people around me that modeled that. So I was always really interested in engineering and technical subjects. There was a one point in my life I just wanted to play music and have a rock band.
Andrew Scheuermann
Right. And then I was kind of one of those people when I went to college that I didn’t know what I wanted to do. I had a lot of energy. I love technical subjects, but I really didn’t know what I wanted to do. And so I went to graduate school because I love to learn, and I was studying material science. So, yeah, it definitely wasn’t until later that I really figured out that building a company was something I was really excited to do.
Brett
Nice. Super cool. And a couple of questions just to better understand what makes you tick and where some of that inspiration comes from. So is there a specific CEO that you admire? And if so, who is it and what do you admire about them?
Andrew Scheuermann
Yeah, so on the CEO side, and sometimes people ask the Founder side as well. Like on the CEO side, I have to go with Andy Grove from intel. He wrote all the books. Like High Output Management. A lot of these fundamental ideas, like one on 1360 stuff comes from that. And John Dore that worked with him went to Kleiner Perkins, wrote the kind of OKRs method for Google. So I love Andy Grove’s original stuff as a CEO, he was CEO Ventel, so he always really inspired me. On the Founder side, people ask that as well. I don’t quite have as many Founder icons. I really love studying culture, so I really love the book Built to Last and like, good degree, kind of Jim Porous Collins and Porous like books. And I love reading about Amazon for efficiency and strategy, or Apple for user experience, or Siemens and GE for the fact that those companies built crazy hard things that are still defensible like 100 years later, which is totally amazing.
Andrew Scheuermann
So, yeah, a collection. A lot of entrepreneurs are first principles people. And that’s like a really important way to see the world, like kind of a physics, like, what’s fundamentally happening in the world. And I studied chemistry before I studied material science. And chemistry is kind of a pattern matching thing. You understand all these patterns, the functional groups and what tends to happen, and there is a pattern matching way to understand a lot of the deep. And I studied economics too, so I was a chemistry and economics major. Both are like pattern matching disciplines. So I think for that reason, I also really love studying kind of cultures and communities as much as I like studying kind of individual CEOs and what that’s led to at a given business.
Brett
And I think Elon Musk is the one who really blew up first principles thinking. Or at least those are the stories that I’ve read and I think that’s where it really spread from a lot. Can you give us an example of you applying first principles thinking to a business problem that you were facing at some point or just maybe an objective that you were trying to achieve as a company?
Andrew Scheuermann
Yeah, and maybe I’ll contrast that with pattern matching thinking, for example. So my Co-Founder comes from a physics background, I come from a chemistry background. So we actually love talking about first principles versus pattern matching and the power of both of them and the limitations of both of them. So like a first principles thinking, where have I used that specifically? So we’re a company that pulls data out of factory machines to do predictive analytics and understand how to fundamentally improve a factory. There’s a lot of things there that follow patterns. All of machine learning is kind of like pattern matching, right? But on the other hand, you’re digging into a given machine and you’re asking what’s actually possible? So a lot of times our customers will say, hey, could you predict XYZ? For a specific example? They’ll say, could you predict why this machine is down for every hour of the day?
Andrew Scheuermann
And from a first principles perspective, you’ll say why understand exactly the data inside this machine and what is or is not possible from any statistical algorithm? Like, do you want to predict why there was a maintenance problem? I can predict maintenance for you based on all the sensor data. There are first principles in the data that should allow me to predict a maintenance problem. But on the other hand, if your machine is down because you ran out of materials, or your team just decided to change the schedule that day and they’re not even running, there is no first principles in the data to predict that. That’s just like very clear. Maybe if you have a scheduling system or if you have a material management system, I could mine that. And it’s so funny how that’s not intuitive to so many people in the factory. AI is this black box and so they’re like, oh, I have no idea what it can do or not do.
Andrew Scheuermann
So they always ask. So anyways, that’s not on business strategy, that’s on product. But it’s a very practical combination of the product that we build is a pattern matching product. And it’s so important to understand the physics of the data, to be able to know what kind of results you will or won’t be able to give customers.
Brett
Super fascinating. Now can you take me back to the early days? You said, what year did you launch? It was about eight years ago.
Andrew Scheuermann
That’s right, yeah.
Brett
Take me back to eight years ago. What were those early conversations like with your Co-Founder?
Andrew Scheuermann
Oh, man. So one big arc of our story is that we pivoted a lot, but we had one particular very large pivot. So the very first version of Arch actually originally called Well Done technology, but we adopted the name Arch pretty early, was a modular IoT platform. So this was 2015, 2016. It was kind of a year or two after IoT platform generally hit peak hype. But we hadn’t quite got that message. We still thought there was a generic IoT platform to be built across all the industry, across the board. And we had this modular hardware solution that was kind of competing with Samsung, had a product called Arctic and Relayer before they pivoted, had these blocks product. So a bunch of these modular electronics projects and that ended up not being successful. We pivoted the business to become a data and analytics company in manufacturing.
Andrew Scheuermann
I could tell that whole story in more detail if we want to go into it. But your question about what was the conversation with the so, you know, early on, were both doing our PhDs at Stanford. I was an experimentalist. He’s a theoretician. I guess the funny story about how we got to be working together, were already really good friends, and we had spent some time living in the basement of a house together. He was prototyping these electronics and other things. I was working at Sternex, and one day he was thinking about ways to expand the business ideas that he was working on with these electronics. And me, with my StartX hat, my kind of helping other companies accelerate and try to get started, I was like, oh, you need another Co-Founder. You need a business partner to come in and help you take this to market and think about the right way to go.
Andrew Scheuermann
And he was like, yeah, I do. And I was like, I’m really good at helping people find co-founders and build teams. Maybe I could help you do that. He was like, oh, it’ll be awesome. And so we actually engaged first on this journey of me trying to help him find somebody to pursue this particular idea that he had. And long story short was we had conversation after conversation and kept kind of figuring out that were each other’s like Yen and Yang. And weren’t just friends in a business partner sense. We were each other’s, Yen and Yang. The things that he was worried about, I hadn’t answered for. The things that I was worried about, he hadn’t answered for. Long story short was one day I’m like, oh, I’m so scared this is going to hurt our friendship. But I send him an email and I go, I’ve been thinking a lot about this, and I think I want to be the business partner that I was trying to help you find.
Andrew Scheuermann
And he was like, I’m so glad you said that. That’s what I want too. So we ended up partnering and starting on the journey.
Brett
Wow, that’s super cool. And then do you want to expand on what you mentioned as well there?
Andrew Scheuermann
Yeah. So the first company has its own very cool story. I’ll try to tell it quickly and get to kind of the second company. My Co-Founder, Tim Burke. Before I was working with him, he was working with another colleague, austin McKee, and some others in a nonprofit called Well Done International. And they had a grant from the World Bank to try to monitor wells in Tanzania specifically to begin with. So think about industrial, think about analytics. Of the many GES over here saying, we’re going to digitize the jet engine, predict everything that happens so a jet engine never breaks. On the other side of the world Bank’s working with my Co-Founder and these other colleagues saying, what if we could predict when a well is going to break and people aren’t going to have drinking water anymore? Could we put a really simple sensor and a cell phone together, make it just as cheap as possible and solve this really important problem.
Andrew Scheuermann
One of the UN sustainable Development Goals, sustainable water for all. So really awesome mission. They’re working on that. And out of the sight of that springs this idea started by Pemberg and Austin McKee that could we have a company that generally sold sensors and got data from machines. It was kind of an early form of this, but the focus was on the modular electronics and the building blocks. So that’s when the story that I just told you happens when I meet Tim and we start working together on this project. And it quickly evolved from wells in a rural setting to wells in California and trying to monitor irrigation systems. And then that evolved to power plants and all kinds of different things. The Unifying footprint initially was these modular electronics. So were actually a hardware developer company. It was like, you can make different building blocks of hardware and we have APIs, you our customers, you’re going to be the developers that are going to use our data and build different sort of AI apps.
Andrew Scheuermann
And that seems like it’s going to work amazingly well for OpenAI with their LLM models. It did not work at all for us with this idea of hardware to kind of data mine for you and you would build something on top. And the reason it didn’t work was because our customers were largely, you wanted to sell a large enterprise and all of them would say, I want to build my own AI models. I want to build my own AI models. But they didn’t necessarily have the capacity, they didn’t have the team. Like, talent is so hard to come by. So they were all telling us, you’re doing the right thing. I need data out of my machines and I want to build all the cool stuff with that data. But none of them really succeeded in doing that. And they didn’t even have the software developers hired and they weren’t hiring them.
Andrew Scheuermann
So it took us a while to figure out why that wasn’t working. Because your customer is like telling you, yes, you’re doing the right thing, but we’re stuck industrial. Everybody talks about POC hell, proof of concept hell, where your big customer, that is hard to understand, tells you’re doing something good and you’re just stuck in pilot mode and you can totally die. And we would have died there. We had really not that much revenue. It was pilot revenue at the end of all this. I think we got to like 300, 350K, not bad for pilot revenue, but nothing significant. And none of that was good revenue. It was all pilot revenue, right? And so we totally would have died on the line at that point. Except that all of these enterprise customers were saying, the end problem we’re trying to solve, we’re trying to get the data out of these machines, do analytics and then optimize X, right?
Andrew Scheuermann
And X was different if this was a factory or it was an irrigation system or it was a power plant, but that thing that they were trying to Optimize X, it was really valuable to improve it. And So it was clear to us that you could build companies here. It was just that the original kind of version of the go to market was just totally different work and we needed to verticalize. So that is the big pivot that we made. We picked manufacturing of all the different things that we could have picked and then we got hyper focused. So inside of manufacturing, we picked forever only discrete manufacturing. So today, Arch Systems is a Data and analytics company that improves discrete manufacturing. And within Discrete, we focused on the high tech end of It. Electronics, electronics products electronics, assembly. And when we finally got that focused on a vertical specific solution, we built the whole thing right.
Andrew Scheuermann
We built the analytics and the intelligence and were able to start providing awesome optimizations inside of our customers. We made a really key partnership with any entrepreneurs out there want to reach out to me? I’ve told the story many times. We’ve done some really big strategic partnerships. So we worked early on with Flex, which Flex, Jable, Foxconn are kind of known as some of the biggest manufacturers in the world. All of those, all the large electronics manufacturers are critical customers and partners. For ours in particular, we worked with Flex early on. We almost did free work for them for a long time and they essentially gave us access to all of their factories worldwide. Really kind of incredible deal for both sides. Both took a really big risk on each other. And with all those factories and all of that data, were able to build a really incredible offering that was optimizing the efficiency of the factories.
Andrew Scheuermann
So I’ll pause there. But that was kind of the first story. Hardware failed pivoted into a vertical specific approach. And then that was about early 2020 when I think it took three years, a little more than three years at that first kind of business restarted. And now it’s been a little more than three years since that Pivot, and we’ve made incredible traction since then. We’re connected to close to 10,000 machines and 100 plus factories, 15 countries working with a lot of the biggest names out there with a product that now delivers a lot of ROI to factories.
Brett
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Brett
But I think when you have a company in the early stages, it’s really scary to make that call and make that decision of this is who we’re going to serve. So what was that like for you and how did you make that decision and what was going on inside your head? Did you have those feelings of being a little bit worried of is this the right niche? Is this the wrong niche? Or what was going on there behind the scenes of that decision?
Andrew Scheuermann
Yeah, I mean, it’s so difficult. Some companies are luckier than us and some are less lucky, for sure. Right. Sometimes everybody has to make these focusing points in their company’s life or they don’t succeed. I could have imagined a company like ours that was like, hey, we should be a manufacturing analytics company. And that was generally a good thing to be. But they built the wrong kind of analytics first, right? Or they made a hypothesis that analytics A will create value, but it didn’t. But then, okay, let’s try BC or D. In our case, we pivoted the market, the product, the positioning from horizontal developer to vertical analytics, we pivoted almost every single piece of it. How were we able to do that? So were much more unlucky than people that start their business right next to a great product market fit, but far luckier than people that don’t start anywhere near a really valuable signal or they’re kind of unable to make a pivot and not get to something that is extraordinarily valuable like we’ve been able to do yet.
Andrew Scheuermann
I think the way were able to do it, make the decision, was just that were keyed in on the value proposition from the beginning. We were really listening to our customers. Like Steve Blank says, were getting outside of the building from day. Like, were going literally into the fields, putting our boots on when it was agriculture, were going into the power plants, were going into the factories. And so in the earlier phase, when were trying to be a developer platform, were not just sitting back and saying, use the technology. We were going into the field with the enterprises, software developers that they did have and trying to help them get their own things built on our platform. And then we ended up knowing the true value of the end customer as well, or better than they did. So when we realized that our customers weren’t going to be able to build their own system, we knew what to do, right?
Andrew Scheuermann
We already kind of understood why is the efficiency of the factory low? How could you analyze it? How could you give someone a dashboard, an alert that helps them improve the Fit? So it wasn’t like this kind of crazy jump where we shut down the company. It doesn’t make sense, right? And so we followed the value again. And then how do we decide on manufacturing and electronics versus the others? Combination of two things. The part that was systematic was we did study kind of the market sizes across the board. Manufacturing was one of the absolute biggest markets. The inefficiency gaps that we had seen in these pilots were the largest by far. So both the market size and kind of the acuteness of our product, like how directly it attacked the value that we could bring and the uniqueness, the differentiation that we had. So our modular kind of hardware side had led us to be really good at connecting many different types of machines.
Andrew Scheuermann
And initially the thought was, yeah, we can do irrigation systems, we can do factory machines, we can do machines in the power plant context. Well, if we had picked like an irrigation system, there’s one or two pieces of it, but then that’s all there is. When you pick the factory is full of ten, 5100 different kinds of machines there. So actually that exact same skill that our developer platform had, which was going to all the different machines and really rapidly making lots of different versions produce data, actually had a great fit with our skills. So big market, big need and connection with the differentiation that the tech investment we had made provided was there. And so that’s why while it was a big pivot, there was no question that were continuing the exact same company because it was also true that kind of we saw the connection with everything we had done, the value of it.
Andrew Scheuermann
This was needed to take us to the next stage. So anyways, altogether that helped us double down and make that decision.
Brett
And can you talk to us about how long it took for you to know that Pivot was going to work?
Andrew Scheuermann
A long time. And I bet a lot of other entrepreneurs out there can resonate with this, that right now we’re well on our path. We’re scaling maybe very rapidly here towards the 10 million arr point. And even now, maybe even when we’re at 30 million, 50 million arr, I will still be like, is it exactly right? We hired a product person recently and I told her that I don’t think you ever have 100% product market fit. And she was like, thank you. I’m so tired of entrepreneurs telling me they 100% have product market fit. There’s nothing else to do here besides build features. And I’m like, no. No way. Always reevaluating that. So in that regard, I would say I still don’t know for sure, and I don’t think you ever do, but I would say we took about a year after we made the focus in, before our customers were really responding, and they were saying, hey, don’t just do five machines, do 1000.
Andrew Scheuermann
And that was obviously a really strong signal that they wanted us to try. And then obviously the second signal comes from repeats in multiple customers. In some industries, you get that really fast because your customers are small. So you get to 100 customers. When our industry and industrial, our customers are enormous. And in the case of electronics contract manufacturers, there’s less than 20 massive ones in the world. And so, yeah, it took us another that first year, kind of 2020 to 2021. And I’d really say to the end of last year, as were picking up speed and getting to more of the largest manufacturers in the world, we had a lot of confidence already six months ago, twelve months ago, that were absolutely on the right track. But still you get more and more big logos, more case studies under your feet, and you have just yet further confidence that we’re truly digging into something big here.
Brett
And how do you think about your market category? So I saw on the website it was described as a marketing optimization platform, I believe. Is that the category? Is it manufacturing analytics? Or how do you think about that market category?
Andrew Scheuermann
Yeah, manufacturing optimization platform. Yeah, it’s one of the words that we’ve used. That’s a really good question. So we sell into discrete manufacturing, and some people like to call it Industry 4.0. The overall kind of trend that we’re a part of, fourth Industrial revolution, we sell to electronics manufacturers, we sell to discrete manufacturers that make cars, planes, medical devices, et cetera. What do they consider us to be? Did they use the word manufacturing optimization platform? No, not really. There’s four things that exist in the market that we often get confused with, but we’re none of them specifically. And I’m sure a lot of other entrepreneurs can relate to this. It’s like when an investor asks, who are my competitors? I don’t say nobody, I’m totally unique. I don’t say that. But I say, which category do you want to pick first? In my case, I say, do you want to compare us to a generic IoT platform?
Andrew Scheuermann
Do you want to compare us to a consultant? Do you want to compare us to what the machine makers are doing themselves because they’re building really cool software on top of their own machines? Or do you want to compare us to what’s called an Mes, a manufacturing execution system? Those are my four, and we’re not any of those because we’re not a consultant. Consultants do intelligence manually with people. They come out and. Do audits, we embed intelligence into our product and run it all the time like a virtual consultant. We’re not a generic IoT platform because we don’t just collect generic data. We plug in to machines like internal protocols. We write a library of connectors or drivers to them and then we pre populate all of the bi applications and analytics for the factory it’s like already built. So we’re not one of these generic platforms that just moves data from A to B and you figure out what to do with it.
Andrew Scheuermann
And likewise, we’re obviously not a machine maker. We don’t make any machines. We do software on top of machines and we’re not Mes. The Mes is a software that runs the factory. It connects to the ERP. Usually it helps manage what job you’re doing right now, how much material you need to do it, which person is at the station. So we observe the factory and improve it. That’s why we use the word manufacturing optimization platform. My view is that we are in a new category and there is a lot of companies that are in this new category that we’re in, which is kind of observability AI analytics on top of a process and many people are coming out with different words to describe know optimization platform is one of them. Process mining is like one that Solonus uses. A lot of people just throw out AI for it.
Andrew Scheuermann
But I think that’s kind of a shortcut, it’s not as helpful. Observability I think is a great word, but it sounds good to It departments and not to anybody else. So that’s why we settled on manufacturing optimization platform. Our customers know we’re for them manufacturing, they know what we’re doing, we’re optimizing it. And yes, we’re a platform, we’re not a machine, we’re not a consultant.
Brett
Yeah, I can understand the complexities. I think a lot of startups struggle with that as well and a lot of founders do. Now when you’re selling this platform, who are you typically selling it to? Does it start with It or is it the CEO? Who is that lead decision maker that you’re speaking to first?
Andrew Scheuermann
So if you or the listeners have chatted or are industry 4.0 space, you’ve probably come across this phrase the Itot Convergence. Everybody likes to talk about this. It being information technology, of course, OT being operations technology and the convergence being they’re being shoved together. They used to operate in silos so it would buy a CRM or play around with ERP and OT would buy some control system, they would buy machines, they would buy sensors, they would buy ovens, whatever they needed to do for their power systems, whatever it was for their specific area. And then Itot coming together because you have an Internet of things system, you have a data collection system. So it’s collecting data on the OT side, it’s providing analytics and value again on the OT side. But it’s often managed by It. The security is approved by It. It is probably also helping build custom dashboards, custom things inside of it, helping deploy it, so it bridges both.
Andrew Scheuermann
And so this is like a huge dynamic in going to market correctly. So that’s a context. And then back to your question. You’re like, all right, who buys this? Is it the CEO? Is it the it? Is it OT? It is all of the above, which is one of the things that makes it challenging. So then the question is, okay, who does it start with and then how does it end up being everyone? And that also it can start on the It side or the OT side. So in our sales, we have pretty sophisticated playbooks to be able to identify in a given customer who are the digitization champions in this particular large? We sell very large enterprise. I guess I should clarify that. It would be different maybe if we sold small factories. We sell factories all hundreds of millions of revenue and up, typically in the billions of revenue.
Andrew Scheuermann
So they’re large departments, multiple factories around the world. So It’s at this particular company, are the champions in It? Are they in OT or are they both finding your initial champion to run the pilot, working with them to spider across the organization and build a collection of stakeholders that are going to work with you and get this thing through the door? And it is surprisingly common that they do have to go all the way up to the CEO COO, even for a pilot approval. So you’ve got to be really good in this space. You can’t be just playing around and get in the door at the Flexgable Foxconn, Honeywell, Medtronic, Apples, et cetera, of the world. Your technology has to be really good. It’s got to get high level approval from the beginning and you got to drive a lot of convergence with these different stakeholders.
Brett
Yeah, that makes a lot of sense. And in your journey, as you reflect on the success you’ve had and it sounds like you’re experiencing a lot of growth, what would you say you’ve gotten right if you had to just choose one thing, one tactical thing that you did that was very smart and led to a lot of this success? Can you think of anything?
Andrew Scheuermann
I would give a different answer if it was like focusing on the last year or the last two years. But since we’ve been focusing on the entire eight year journey, I talked about how we’ve done some strategic partnerships and were willing to work for a long period of time with a customer to get things right. In our case, we wanted to go to market an enterprise. And so we structured some deals that were pretty innovative, pretty different, pretty risky, but caused us to not be able to put revenue numbers on the board for a while, but succeed in getting to a ton of factories and having access to a ton of data and expertise that most companies were not able to do. And I guess if I’m going to use that phrase, first principles thinking here, the first principles of it was that we had measured the utilization, the efficiency of these factories, and we knew how low it was.
Andrew Scheuermann
So we knew that if we could build the right analytics tools, we could create massive value. And if you create massive value industrial, everybody buys it because they need that value. It’s not a question anymore. It’s like you’ve shown it, you’ve proven it. And so I think the thing that we did really right is we didn’t build vaporware. We didn’t go out and try to sell vaporware. We hacked this Pilot Hell that everybody talks about. We went into the most Ultimate Pilot Hell you’ve ever seen with some key customers, but by doing so, got access to all their data. We got enough funding to kind of last us through that period. And we built a hell of a product that works at the enterprise scale, is secure and creates a ton of value. And now we have this just really powerful story that we’re bringing out and now we’re being able to fine tune that Pilot speed and tighten it tighter and get through Pilot faster on top of a product that is just a lot more proven than we would have had otherwise.
Brett
And how long are you spending in what you call it, Pilot Hell? How long are you spending on average there?
Andrew Scheuermann
Well, that Ultimate Pilot Hell was literally like a three year period. So that’s why I said it was like the longest pilot ever. We went into ultimate pilot hell, so to speak. Just recently we got through Pilot with two multibillion manufacturers into recurring revenue deals in four months. And our goal is to get that to two to three. But yeah, went from three years to about eight months on average as were starting to sell the motion. The most recent ones were about four months. So that’s just a dramatic acceleration and these are large deals. So four months for the size of deal that we have is a very good time.
Brett
Wow, that’s amazing. Now, last question here, since we are getting close to being up on time, let’s zoom out three to five years from today. What’s that big picture vision for the company?
Andrew Scheuermann
There’s kind of two dimensions of the future of Arch. One is adding what we call cores to our platform. So a core is the combination of the connection to a bunch of machines. How do you get the rich data out of a specific set of machines? And what we call insights, which are this pre built library of analytics dashboards predictive analytics that improves it. So today we focus on surface mount technology and injection molding. Plastics is one that we’ve more recently expanded into and so in the next three to five years we’ll be in far more than two of these core processes. We don’t have an exact order that we’ve announced but cores that we study include CNC machines, they include semiconductor, packaging, paint shops, et cetera. So there’s like many other areas of discrete manufacturing that we’ll be moving into and building these cores on and just having just broader and broader coverage.
Andrew Scheuermann
That’s the breadth part of the future and then there’s the depth part of the future where we make these fundamental technology bets. And we’ve done this already on the machine data platform itself that manages rich event data in the factory. This global OEE system we have that achieves this efficiency scores and understanding of OEE in a scalable way across a large enterprise. The third. We just announced our next technology. Bet is called Action Manager and it’s an intelligent system that helps automatically alert on the conditions happening in the factory, send it to the right people and lets you build these knowledge playbooks where the factory experts have a place to put all their knowledge, connect it to the signals that are happening in the data and it allows you to run a factory in a fundamentally more scalable way in a world where you can’t get top talent factories anymore.
Andrew Scheuermann
The next big technology bet in our roadmap is called Process Explorer. And already today we do some analytics that cross sets of machines. So you combine two, three, four machines data altogether and find analytics at the intersection of them. But there’s a grander picture of this which relates to this concept of the digital thread where a given product is built. I mean, think about a car, think about an airplane. How many different pieces have to come together, thousands in some cases. And each one of those is built in a given factory on a given set of 3510 machines. And so you can imagine the threading together of data just massive kind of organization. But how valuable could it be if eventually you could say whether a given airplane is having a problem, kind of the GE jet engine thing, but the whole airplane, where does it go back to in the factory?
Andrew Scheuermann
So our next big technology bet is called Process Explorer and we haven’t announced all the details of it, but this is where we create some of the fundamentals for this digital threading across sets of machines and factories as you’re building up larger things, not just like an individual circuit board or piece of plastic.
Brett
Well that’s smart Andrew. Now you left us wanting more so we’re going to have to bring you on for round two to talk about that when it rolls out.
Andrew Scheuermann
That sounds great. I appreciate it. Brett.
Brett
Awesome. Andrew, thank you so much for taking the time to share your story, talk about some of the lessons that you’ve learned along the way and really to share what you’re building this has been super fascinating. I really enjoyed the conversation and I learned a lot, and I’m sure our listeners did too. So thanks so much for taking the time.
Andrew Scheuermann
Thanks for having me. Take care.
Brett
All right, keep in touch. This episode of Category Visionaries is brought to you by Front Lines Media, silicon Valley’s leading podcast production studio. If you’re at Peter Be, Founder, looking for help launching and growing your own podcast, visit frontlines. IO podcast. And for the latest episode, search for Category Visionaries on your podcast platform of choice. Thanks for listening, and we’ll catch you on the next episode.
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