Sometimes you have to be deep into a specialized industry to truly understand the areas needing solutions. As a teenager, Arjun Patel was racing forklifts at his dad’s factory. In college, he was a plant manager focusing on quality, safety, and production optimization.
After college, he became a manufacturing consultant. Growing up on a factory floor and learning its myriad intricacies gave Arjun the realization that there were no software solutions to track production lines. “Everything was manual,” Arjun says.
“There’s huge binders tracking logs of what was being done.” This eventually led him to co-found WorkClout, a tech startup that offers a software solution for automotive engineering teams to improve quality.
More information: https://www.workclout.com/
WorkClout is a quality management platform for automotive parts manufacturers. Our software helps streamline & automate internal audits, document control, visual inspections, training, and preventive quality design.
Arjun Patel is the CEO of WorkClout, a venture-funded technology company that provides quality software to the automotive manufacturing industry. He is the son of a manufacturing owner and was a former management consultant and growth product manager. He currently resides in Los Angeles and focuses a lot of his attention on quality design and strategies for industrial sectors.
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Arjun Patel 0:00
Like what a year P is doing, it’s, they’re trying to do everything at once and optimizing the whole workflow, which like makes it cumbersome and you know, you’re just gonna, it’s Lisa failure after that.
Alexander Ferguson 0:14
Welcome to UpTech Report. This is our applied tech series UpTech Report is sponsored by TeraLeap. Learn how to leverage the power of video at teraleap.io. Today I am joined by my guest, Arjun Patel, who’s based in LA. He’s the Co-founder and CEO at WorkClout. Welcome, Arjun. Good to have you on.
Arjun Patel 0:32
Good to be on I’m excited to be here and excited to you know, share a little bit about my story and hopefully inspire others to take the same journey. I’m
Alexander Ferguson 0:41
now starting a tech startup is not a small thing. But what you guys are focused on at WorkClout is quality and safety management, specifically in the manufacturing industrial industries. on your website says mistake proof your quality process. Help me understand that like where did this start for you? I’ve in our prep chat already. I feel like you said it was actually with your dad who was or in in industrial and manufacturing. You saw some of the problems like how did that lead to you starting workclout?
Arjun Patel 1:07
Yeah. Yeah. Yeah, thanks for asking that question. This, this really began when I, I Oh, like my like to give you a little bit of background. My father, he started he, he immigrated to the US in 1985. And then he started a manufacturing company, he was owning like a bunch of other stuff, like he owned a carwash and a liquor store. And eventually, you know, he started working on a manufacturing company. And it took him like, two to three years to get into, but he started that in like, 1995, and the companies started taking off around like, 1997. And then now it’s like a 500% operation. And throughout the years, you know,
Alexander Ferguson 1:49
were you involved in like, early on?
Arjun Patel 1:51
Yeah, I’m early on. I was a baby. I was like, a little kid. Early on, but but as a part of it, yeah, as it grew, I was I was very much like, a part of it, you know, most of my friends would be hanging out biking after school would be, you know, in the factory, like racing on, you know, the the forklifts. So, you know, I learned about not not really safe, but for the most part, you know, I, like I was, I was very much in that environment. So it was a lot easier for me to pick up problems within the environment, you know, and I know, like, as I got older, I realized, you know, this was a very specific, like, the problems I was thinking it was very specific to my dad’s manufacturing, or that’s what I thought initially. And, and I got into consulting right after college, because I worked at my dad’s factory. When I was in college, I was like a plant manager. And I focused a lot on the quality optimization, safety optimizations, and even like, production efficiency optimizations. And, you know, we really, really never adopted software or any type of technology, everything was manual. Like, there’s huge binders, tracking logs of like, what was being done. And, and then the way that they would track like a job going through the production line was like just a giant folder, that would be like step one, all right, what’s what’s happening in this job, and it would be written, obviously, a lot of mistakes happen because of that. And when we approach these European systems, like, I remember, we were trying to approach like other European systems specific, my dad’s manufacturing industry. And it, it was just very, like, expensive, you know, it was like, $200,000, just to get started. And then you have this crazy maintenance fee. They had to pay and then everything was on premise, too, right? So anytime you needed to upgrade, you’d have to pay for pay for those upgrades as well. So my dad, he didn’t really see the ROI back then. And then he heard horror stories from all these like software integrations. So your pizza Yeah, like give it a bad taste to the manufacturing industry like well, is to a lot of costs a lot on premise. It’s horror stories are connected to it. So then you’re like, Alright, there’s
Alexander Ferguson 4:06
gotta be a better way to do this. Yeah,
Arjun Patel 4:09
yeah. I mean, that’s initially like, you know what I was thinking, right? Because when you’re trying to do, at least in the manufacturing industry is like, they’re trying to do everything. They’re trying to optimize every part of the digitization workflow. But it’s just very hard to do that with one software. That’s what I think there’s been an increase in virtualization of software, specifically about certain use cases, you know, like you have maintenance people want to focus just on like maintenance. Software, you have like, production like MBs is like me S is manufacturing execution system. And what that means is it’s just focusing on the production side. And now like, you know, what I’m creating is it more about the quality and safety because that’s like another part like the AARP does have these components, but you know, it. It’s like if you’re trying to build everything, nothing really is the like investment. I may leave it may leave you wanting more if it’s just a small component of a much larger system. So you want Yeah, he called in and Bill justice offer around safety and processes. Yeah, yeah. I mean, like, I read the story about this one steel manufacturer called Alcoa. And what they did back in the 80s, was, they only optimize for one thing. And one, once they optimize for that one thing, they ended up tripling or quadrupling their, their market value. And Alcoa is like a, like a public steel manufacturer. And the new CEO came in and he said, Alright, I just want to focus on one thing, which is safety. And that’s it, and they just focus, they just optimize for safety, nothing else, because they have the highest entry rate above like normal in their industry. And he came in and then within like five to six years, they became a multi billion dollar company, because they just focus on safety, because focusing on the safety aspect of it had compounding, compounding effects, like people were more careful about how they did things. So quality increased, and because quality increased, right, like the the reputation increased, and you know, more people came to them. So it was just like a micro change. You really believe that safety is like the foundation of a successful business,
Alexander Ferguson 6:24
if you put safety first the quality outcomes will follow.
Arjun Patel 6:29
Exactly. So you know, it like there’s a this phrase that a lot of people use manufacturing or like continuous improvement, but what continuous improvement is it’s small changes make big results. And a lot of people think they have to over like over architect the workflow and do the things but honestly, it’s like focusing on the area of highest opportunity or lowest hanging fruit, and then working from there and doing experiments to optimize other areas. But if you try to, like when an ER P is doing it’s they’re trying to do everything at once and optimizing the whole workflow, which like makes it cumbersome. And you know, you’re just going to it’s Lisa failure after that.
Alexander Ferguson 7:09
So you’ve got to two years in three years in 2018 2019 is when when you when you started we’re cloud actually yc combinator, what went went through that? Yeah, Y Combinator, but how did it like the beginning, the antithesis, you immediately see a resin a resonation, with with manufacturing, saying, well, we this is what we need, or has a bit a more of a slower adoption, because of the the history of the RPS and like whole technology. Do we really want this in manufacturing? Yeah,
Arjun Patel 7:39
I think that’s one of the biggest things about like, I know why it’s, you know, there hasn’t been as much software because there is some sort of reluctance for manufacturers to adopt software. And you’re completely right on, on that statement. europese they sort of scarred manufacturing companies like even today, when I’m doing demos or sales calls. I’m still hearing like, Oh, you know, what, what’s the on premise maintenance fees? What’s good? I was like, no, we’re not on premise. And like, there’s still a lot of them are still afraid of cloud, but they don’t realize they use Cloud every day to write and like their everyday life. And. And I honestly think like in the 90s, a lot of people in the 90s are still working in the same manufacturing companies, at least from like, my experience, and they’re long, 10 years with many factors, like the average age of a manufacturer is 56 years old. Right? So they’ve been working like, in that industry for a long time. And so much has changed within that industry. And in terms of technology, since they first get started in there. And I think in the 90s, they were very receptive to software. And that’s where the earpiece came in and totally ruined their perception of software, but it is getting better, especially I think, after COVID right, like, the pandemic, I think, they were still reluctant during, during the pandemic, but now, like they see the value of how software could actually, you know, streamline a lot of the processes, especially if not all the personnel are there. And there are other crisises is going on in manufacturing such as, you know, skills gaps, people negative rate replacement, from people retiring, and I think they’re beginning to know that they’re beginning to realize, like, you know, software will help streamline like at least have tribal knowledge. So we could operate with less people, when things are more systemized and, and that’s why I think the adoption curve is actually increasing. And you just have to give them a specific use case. I think that’s like, the biggest thing is, if you if you try to optimize everything, because I remember in the beginning, when I first started the software, we were trying to optimize their production, trying to optimize like almost kind of replacement. yarby just making it user friendly. And then we ended up iterating and iterating until we got to, like the simplest thing, which is like how do I optimize quality and, and that’s what we’re focused on today.
Alexander Ferguson 9:53
It’s a powerful component of realizing to focus on one granular, let’s just get this one working really well, and safety help me understand a use case like in play? How does your platform how’s your tech work?
Arjun Patel 10:08
Yeah, yeah. Um, so I guess the simplest thing is like, what we try to introduce them to is just replacing their, like Excel, PDFs and other forms that they’re filling out already. And, like their existing process right now to do like, let’s say they want to do like a quality visual inspection, I have this engine, and I have to make sure this engine checks out. You know, I have to make sure that all like it’s it’s not, it’s conforming to what is considered normal, right? So I’m going manually on like a piece of paper thing. Alright, check, check, check. All right, it’s on to the next one, right. And what that leads to is a compounding cost of quality issues, right? Like you might miss a check or, you know, things might not get escalated, because they’ll write defect, but no one will see that defect on that piece of paper until like the end of the line. Because it’s not getting escalated on time. So Well, our software is doing at least like in the like, I guess like the most simplest use cases, digitizing those forms and making it a little bit more automated. So we’re adding a lot of more automation workflows. So let’s say if something is notified that it’s non performing, like they’re, they’re, they’re inspecting an engine, right and something like goes wrong with the engine, instead of someone having to look at it like later on or them having to look for a supervisor, everything is escalated and the appropriate time to actually address that issue before it goes
Alexander Ferguson 11:34
further along in the supply chain. So basically, someone there is standing before this engine like yeah, this doesn’t look right, there’s a problem, they basically check off something a button that sends off an automation that notifies the right person like, hey, this needs to be looked at, and then they can come over while that person can move on and continue their job.
Arjun Patel 11:50
Yeah, yeah. And like what we’re working on right now is, we’re trying to even make it easier for like the technician or operator or engineer to visually check it, instead of just relying on their eyes, we’re actually incorporating more camera technology to automatically identify it. So we’ll run like a machine learning algorithm on like, what, what is considered, you know, a good engine with no defects versus a bad engine. And then, instead of them having to actually visually check it just themselves, they could take a picture of it, and our system will tell them what’s wrong with that particular engine.
Alexander Ferguson 12:26
Interesting. And is that is that live today? Where they just basically take a picture with their phone, and then it gets loaded into the app? Like, how, what’s that process look
Arjun Patel 12:33
like? Yes. So I wouldn’t say that live today. That’s something that we are working on, because we’re trying to over I guess, I would say that’s like the next edition, we are doing a pilot a few pilot programs for with enterprises on that particular feature. And that’s something that, you know, we wanted to take it to the next level, like what would make it easier for someone to inspect something or to actually control their quality preemptively and not have to rely on like human error, you know, and it’s more of an augmentation than like a replacement.
Alexander Ferguson 13:01
It kind of actually makes me think of how vision, computer vision is being used in radiology with humans be able to say, okay, what’s wrong with this issue? Why not apply it to the same in manufacturing? I, you still have a person that can look at it and make the assessment, but a computer can go through it? And maybe in fine details that a human might miss?
Arjun Patel 13:22
Yeah, exactly. That’s, that’s a great analogy. And that’s sort of our thought process, too, right? Like, a lot of people like they want to know, like, how can software not just like 10x their workflow? How can they 100 exit, right, where, you know, things are really being mistaken proof. And that’s what we’re trying to do. That’s like, that’s why I put mistake proof your operations, because, you know, we want to make sure that we give them the tools to completely, you know, streamline and mistake proof that operations.
Alexander Ferguson 13:51
So let me let me take us in a direction here, if I may, yeah. But automation and technology, we’re we’re getting to an era of where technology really is automating almost everything. And so the question can be asked, well, won’t an entire manufacturing floor just be completely automated? Like, what where do you see then the balance of both automation and, and, and humans come into play?
Arjun Patel 14:17
Yeah, I mean, I think, um, I think right now, like, we’re probably not the area where, you know, robots and everything is, is completely replacing the human. I think the level of skill is, is just needed. I think there’s a higher need for people with more, more technical skill sets, and the like, that’s what’s increasing. And I think like, you know, like, very manual repetitive tasks will be automated, but things that require critical thinking and continuous improvement won’t be replaced by robots. They’ll be replaced by people who have, you know, more skill sets to actually do their job. And it is very contentious, especially in manufacturing. You know, they’re there. Like, everyone’s afraid that robots now replace their job. And you know, it is going to happen. I wouldn’t say anytime, like within the next five years, but it’s going to happen, like, like in the next decade or two.
Alexander Ferguson 15:11
But you already mentioned that there’s a negative rate of replacement in manufacturing already. So it actually, we actually need more automation in order to keep the status quo.
Arjun Patel 15:21
Yeah, exactly. I was reading a story. In Japan, a huge portion of the Japan’s population is elderly. And they’re, there’s a labor shortage in terms of retail work, and how they compensated for that is everywhere. In Japan, you’ll see a vending machine, like a vending machine for food, a vending machine for like, you know, just like picking up appliances. And that’s already starting a trend, like wonder is a negative replacement. If there’s not enough, like labor to, to like, replace people in jobs, then you’re gonna have to resort resort to automation that’s going to happen right now. Eventually, that’s what I say it’s going to happen in the next like, decade or two. But I would still say that there is still a need for critical thinking because like robots, and machines, and like, you know, computers are not the level where they can have, like supreme critical thinking as a human
Alexander Ferguson 16:13
just yet. What another shift of this conversation, it comes to manufacturing, which is this gets, I don’t really wanna go that political, but it will mean you actually go overseas. I mean, like, well, we’ll meet in factories, yeah. What are your thoughts on that? Have you seen?
Arjun Patel 16:28
Yeah, I mean, some industries, it makes sense to have overseas, right? There is like a concept called nearshoring, where people are operating in Mexico, and like, the cost of labor is obviously higher. But even like, in China, people are not even manufacturing in China as much anymore for certain areas, because the China’s middle classes increasing, and their wages are going up. And like, I know, the Chinese government’s like, sort of trying to subsidize it, where, you know, people can still have a cheap cost of living, where the labor, like they’re trying to, you know, manage the market, but eventually, you know, gadget economy is gonna grow over there. Yeah, I mean, it’s like, it’s one of the fastest growing economies right now. And the manufacturers just get more expensive there because of labor costs. So now you have like, Vietnam and other industries, I would say like, clothing, textiles, a lot of these types of industries are being outsourced. But things that, you know, like, for instance, we focus a lot on automotive parts manufacturers, and a lot of parts do get manufactured overseas. But there are some components that people want like more quality engineering, right? So that you have like a lot of European based ones, a lot of us based ones like, Tesla does all their in house manufacturing themselves, but then, and they want to source American parts. And there’s some regulations that needed to make sure that they’re only sourcing American parts. Like, there’s a few companies like Vichy borgwarner, they have to, because of regulation, they have to stay in the United States, or they have to source from the United States. So
Alexander Ferguson 18:05
interesting. Now, now, as far as as this technology, growth and the way people are using it, you we’ve already talked a little bit about this slower adoption, in the manufacturing space. But yeah, it’s changing but if anything, but then the pandemic has been accelerant of our area. We got it we got to bring bring more tech in into it. Yeah, we’re all in the future. What can you paint kind of what you’re excited about the roadmap and of where everything is heading, of being able to use technology in in in helping with processes and keeping people safe in manufacturing?
Arjun Patel 18:44
Yeah, I think it’s going to be very again,
Unknown Speaker 18:46
I remember I’m,
Arjun Patel 18:47
I’m already seeing seeing it with HoloLens. I feel like that’s like, it’s just a hard hat with, like AR and VR technology. I feel like it’s gonna be more viral related or economic related, like I was reading how Tesla was able to increase their safety. And one of the biggest improvements is they visualized like what their workers were doing. And they realized, like, the reason why the rate of injury was increasing is because the ergonomics, so I feel like it’s going to be a lot of like biotech or body, body tech that’s going to help with safety and quality. And even like a lot of the stuff in manufacturing, it’s going to be like an extension of their body with technology, and that’s how I see it going is more bio biotech and agronomic related like exoskeletons, stuff like that. Do you have
Alexander Ferguson 19:38
plans of integrations with more wearables and other content to be able to pull in? Or is it Oh, or do you see as far as a roadmap for for for you guys is more of just it’s a workforce enabler meaningly to do they’re able to automate the the specific tasks or do you see growing into more integrations?
Arjun Patel 19:59
I see. Going into more integrations like because one thing we want to do is we want to empower workers not necessarily replace them. So I like to say like, our system is more augmenting what the what they can do, it’s almost adding like superpowers to what they could already do. And it makes them look better too. And that’s what we want to do. We want to make them look better. And the more tech that we could augment their abilities and make it more seamless, not like intrusive, the better I think, you know, like society will be at least in manufacturing.
Alexander Ferguson 20:30
I love it. I love it. I just just for fun if you could wave a magic wand, and have any futuristic technology come into existence right now. What would you have
Arjun Patel 20:42
teleportation 100% I even had an idea like, like company we call it quantum for quantum entanglement, because it’s teleportation, because so many use cases it probably destroyed a lot of industries if it was introduced today. Right. But, but I was thinking about like, there’s so many use cases for teleportation like and like, we wouldn’t have a resource constraint because we’d be able to teleport to any part of the universe and even get resources from anywhere. Like we have unlimited resources at that point. Right. And I think it would change our society like even like culturally, you know, technologically, you know, it’d be a lot more prosperous if we had that one technology. So that’s that’s one. I would love to have.
Alexander Ferguson 21:24
teleportation Yeah, Beam me up, Scotty. I think everyone can appreciate that one. For sure. Well, thank you so much for sharing your journey that you’ve been on in many ways. It’s just beginning. But a painting a future of a safer work place using technology augments workers to be able to be more efficient and safe at the same time. For those that want to learn more as you go over to workclout.com. That’s WORKCLOUT.COM and looks like book a demo. Kinda like explore is a good first step for people to take.
Arjun Patel 21:58
Yeah, that’s an excellent first step to book a demo, you might even be in contact with me. So they want me to walk you
Alexander Ferguson 22:05
directly with Virgin. Well, thank you again for your time. That was good to have you on and we’ll see you all on the next episode of UpTech Report. Have you seen a company using AI machine learning or other technology to transform the way we live, work and do business? Go to UpTech report.com and let us know
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