Scaling Warehouse Automation with Robots Demands Alignment, Education, and Collaboration for ROI Success

Alright. Very good. Good morning, everyone. Josh Kavanko here, Vekna Robotics' chief marketing officer, and welcome to episode five of robot versus wild. I'm joined by yet a new trusty pal, Tyler from Voyage, our customer success manager. Ty, welcome to the show. Thanks, Josh. Great to be here. Awesome. I know you've had a busy morning already and a busy week. Thanks for joining. Just to level set everyone, this these episodes are all recorded. You can obtain them on our website, and even get little snippets. We started to produce little snippets for all the webinars going back two years. So if you just wanted to listen to a one minute version or a ninety second version there there, this one will be available shortly in that format, but also, as a full fledged replay, if you register. So, with that, if you just to remind everyone, what's robot versus wild about? It's really about scaling your automation program, and that's why we have, Ty here today. And the title of our program today is there are no bad robots, only bad owners. No bad robots, only bad owners. So we'll get to that in a second. But let's our normal tee up. You know, what what what is what is this series about? And then we'll we'll include you, Ty. Okay? We'll bring you in in a sec. Alright. Yeah. Awesome. So like we always start or how how we've started this series, the technology in warehouse and distribution, has differing degrees of maturity. And we what we wanna convey to you and everybody out there is that the techno there are some technology that's ready for prime time and other technology that you may hear about that's still a little ways away. Okay? And we to in this series and today, we'll really focus on the technology you can obtain today. Horizontal transport, person to goods, good to good to persons, picking, like, Glocus, cube storage. That's that's ready for prime time. Okay? Some of the other technology that you heard underestimating flexibility, that's a big one, and Ty will get into that in a minute, and integratability. So just because you have a proof of concept or you've tried it in one spot, can it flex over to other workflows? Can it integrate, with other systems is really important. Support is another one that's really critical. Underestimating the impact of deployment on changing scope and cultural factors within your facility. There's people. You're working with people. Your needs change. Your business needs change, and they're changing fast. Can the technology handle that? Weak goal alignment. So we're gonna get into that right away within a facility. That I would think is one of the top, pitfalls to scaling your automation program. And then failure to forecast, a changing warehouse landscape over time. Like, where where is your particular industry headed vis a vis where I was in distribution. So to us, those are the key elements, that really stand in the way to scaling automation. I mean, Ty is gonna talk about more day to day, issues that prevent scaling and prevent immediate success. But longer term, these are the things that we encourage prospects and customers to think about as they're contemplating and choosing, choosing a vendor. Okay. So that's my my standard setup. I just wanted to now, I've introduced Ty, but I wanted to give him a moment. Ty, we're talking about their, the title for this this, this webinar, there are no bad robots, only bad owners. We're not being judgy, are we, Ty? Are we being too judgy here? What are we talking about with this title? No. No. Not at all. So what we're talking about so first off, my team, is customer success. We come in after your robots are deployed. Yeah. And we work with the sites as a partner. We help with troubleshooting, adoption, any sort of expansion, adjustments that need to come after the deployment. We're there to help the learning curve go quicker and overcome obstacles with the customers. So this title, I will say right now, we don't have a bad owner. All of our customers we work with are fantastic. This is really just comes from this is a very new technology like you're saying, Josh Mhmm. For a lot of these warehouses. And it's the learnings, the, changing of processes that have been established to incorporate, the automation of the facility. That's what we're really going for here. Right. There's also a level of comfort with the technology and so on and so forth. And by no means is the technology perfect. No technology is perfect. Right? Like, my, my car had a recall just announced a few days ago. Like, no technology is perfect. But the idea here is that it's really about people adjusting to the technology as well as the the technology adjusting to the people. Okay. So we've got so that's our title. For better or for worse, that's the that's what we're working on, Ty. We're not going off piece here. We're gonna stick to it. I think we've got six or seven narratives that that Ty has put together that I think will help round out the story here. So let's get to it. I'll just flip the slide here. So here's the first one, site alignment versus headquarter alignment. A big one seemingly a no brainer, but it pops up more, you know, more often than not. So so how does how is this an inhibitor to, to scaling automation when this site and the headquarters aren't necessarily aligned in your world, Ty? Yeah. So this is actually a big one we run into. And it's both headquarters and the sites. Both are looking for the best way to optimize the robot, to get the most value out of it. Yep. And, really, we use the thing, what does success look right look like for each? And it corporate may have their own vision, what they believe success looks like, and the plant that more day to day operation has their own vision. So it's one of the first obstacles, my team looks to adjust or, go after when we bring a new client on is getting that alignment all the way from corporate to site leadership to floor leadership. Make sure we're all chasing success the same way, and then we can set up our milestones, our plans of attack, all of that with the one common goal in mind, knowing what success looks like. Yeah. Very good. And, you know, our as we as it says here, you know, our best sites see tech as a as an enabler. They want more data. They're always looking for more data. And then, you know, the the ultimate sites have champions at both excuse me. The old the best our best customers, have champions at both the site and the HQ, and and and your job is to really help navigate that. We were on a livestream last week, Ty, on our LinkedIn live, and I think I called you a Sherpa, right, or a shepherd. Sorry. A shepherd. You're a shepherd within the customer. Right? And sometimes even calls negotiating what headquarters has asked have asked us for and then what the site needs. Right? Yes. Yes. Alright. So on to the next. This one's fun. What are we talking about here? There's two elements here. You know, here's the the famous Rolling Stones, song. We can't always get what you want, but you get what you need. What are we talking about there? Yeah. No. This is probably one of the biggest obstacles that we have to overcome, and we like to word it as keeping the main thing the main thing. So whatever the goal the main goal you're trying to accomplish with the technology, whether that be a throughput goal, so many, pallets delivered, taking over a particular workflow, understanding that's the actual goal. That's what you want. And then what and that's what or that's what you need. What you want is how do we accomplish that? And sometimes we find that our customers get too hung up in the want. How does this happen? What pass do we take? Operational constraints that will actually always prevent us from hitting that goal, the what you need. Right. The best example we have of someone doing this great, we had a facility. They had some new equipment coming in, and they had to remap. And they called us up. They got we got our engineers, and they said, here's a couple limitations, but the rest pretty much operate in this box. Come back and tell us the best way to do this with your guys' expertise. And they gave us their goal. By allowing us to have that freedom, we were able to ensure that we were able to reach the goal that they had set in mind, where too many constraints would have prevented us from being able to do that. That's why we always start thinking, what is your ultimate goal and allow us to reach that for you? Right. And so that ties into, what you want the robots to do may not and the way that you want them to do it may not be the best way to do it. So that's what that's where we come in. Right? But then there's the other side of it, the right side, this ridiculous guy. Vacuuming is long. There's the other side is what what you want may not be what robots do well. Right? So it's kind of foolhardy to say, okay. I want robots in and I want them to do that. But if we find things that the robots are better at, right, wouldn't you want to to achieve same or better outcome? Isn't that what how you you should be deploying it? So, talk through this one, Ty, this ridiculous one here on the right. Yeah. Yeah. Absolutely. So where we'll see this, one of the more negative examples is people get hung up on a KPI. We have to have so many moves this month. So they will look to set up, maybe a move or a use case that only has the robots traveling fifty, a hundred feet. It takes more time for a manual operator to stage the robot, go through the process either setting up in the WMS or calling the robot. Then it would've been just to complete the work themselves, but they're looking on that KPI. It's a very rare, but we do see that every once in a while. But where we really see this, and I love it, is when customers get really excited about our tech, and they wanna push the boundaries, push the barriers, figure out where failure is. What are the robots truly capable of? And I'll say they push our technology way further than, we I thought it could go. Really helped accelerate, a lot of our development. Yeah. But, again, we do sometimes when we do that, start to take away from what the robot's true capability is, what the main thing was. And that's kind of thing. It was keeping the main thing the main thing. Right. Okay. So, clearly, the vacuum cleaner, it wasn't designed to do this, and it probably doesn't do it really well. Although, the lawn is looking pretty good. Yeah. It's good on the lawn. But to the point to your point, right, yes, that vacuum cleaner or the robot may do may may produce interesting outcomes or good outcomes here. The lawn is beautiful, but that's perhaps a suboptimal use of a robot or in this case, the vacuum. Right? And that's that's really what Ty is trying to say here, right, in terms of, is was that what the robot was intended to do? Okay. Let's move on. I think we've we've bludgeoned that one to death. You talked about KPIs. This is seemingly a no brainer, but I would I would like to assert that, Ty, your job would probably be a lot easier if it was a no brainer because it's not. So let's walk through why it's not the no brainer that everybody thinks it is that you have. No. I mean, our team really pushed for this. This again goes back to what does success look like. Yeah. And I think a lot of companies are really excited to get the technology in. They see the potential of it. And then when we start to ask the question, what does success truly look like? It's Mhmm. Well, where are the defined goals? What really are we tracking? What is some a metric we can hold the robots accountable to? What is site influenced? How do we really work that? And then we found a lot of our customers, and I truly do believe this is just because of timing, didn't have any thoughts of this, but that's because they were buying during the COVID pandemic when they couldn't get labor support. So success was keep product flowing in any way possible. Good. And the MRs were succeeding that. But now that that's kind of over and winding down, success has changed. And that's one of the crucial things my team does and what where we find our values. Success will always change. Warehousing is dynamic. Demands are dynamic, which means success and goals are dynamic. We're always there to help pivot and adjust to make sure we're adapting with facilities. Right. But that's different than not having goals. So let's be clear here. We understand that folks come in for for the first time. They're working with the technology for the first time, and and then they deploy it, and then things sort of change. Our job is to help you keep your eye on the prize. But we're once again, Ty, we're talking about scaling the program. You will never scale your program. Right? If you're the champion of an automation program within a facility or a network of facilities, right, this program where are is gonna go nowhere. No one's signing the check for the next purchase if you do not have clear objectives with the program and that and we are helping you track to that. Okay? Absolutely. Time and again time and again, we're seeing folks come to us under whatever circumstances, COVID or whatever initiatives there are. Automation to automation state, fine. You know, we'll we'll definitely do that, but we're now conveying our advice to you. If you wanna get serious about scaling a program and be up there with the best in the world at doing this in distribution and warehousing and manufacturing, you gotta have really crisp KPIs about what you're doing here. Right? Because at the end of the day end of the day, this is getting inspected, and, and validated, and and that's really what we're driving for. And Ty's team is really there to validate value. Alright. Let's keep going here. So so you've got alignment, headquarters site. You've got understanding of your of your KPIs. You understand what the robots can do probably a little bit, maybe not forcing the issue too much. But then, well, why aren't the robots performing the way that I want, Ty? You know? Like, how come I can't how come I can't see more productivity out of them than I thought I would? That get gets back to the title, everybody. It gets back to the title. You can blame the robot, but oftentimes and most of the time that tie when Ty gets into it with customers on a biweekly basis, he's speaking to customers weekly or biweekly. It's not always about the robot. Right, Ty? What is it about? Why aren't they seeing the perform when you're speaking to customers every day, generally speaking, what is affecting the the automation performance? Yeah. It's I mean, probably the biggest thing we see, especially early on, is the understanding of how the robots work. And when we take a ten thousand foot view look at these, the robots are nothing more than a tool, a tool to help you get your productivity. And like any tool, you gotta know how to use it and how that tool works. And we see this, and you can see the examples, listed around the picture here, Josh. But understanding the standoff distance robots require, how the lidar's view, how the travel path gets planned, predictive modeling, things like that. And we see the sites not have that full understanding. So they're not trying to be malicious. They'll stage stuff. Maybe in Isles Titan, they think I can get my manual truck through there. Why can't my robot make it through there? Well, that comes back to the ANSI b fifty six safety standard AMRs fall under. So explaining, hey. We need this x amount of distance, in this situation on the side, or the robot's not stopping. Well, no. Coming down the intersection, it's actually safer for the robots to do a slow roll because that allow the human drivers to see it based on how it does its predictive in its safety field, looks around corners. So really getting down to that layer and letting really educating all the floor workers, the supervisors, how the robots work, that really is how we overcome this boundary. Right. There's also like, we do things like heat mapping that Ty has access to that we do at a global level, but we also do at a site level to be like, oh, no. Maybe we need to orchestrate the the work work a little differently because there's too much density happening in one area. We need to distribute the work. And we have connectivity up there. Right? Are are all these warehouses set up? You can go back to our episode last year. I think it was sometime in the summer, June, July, or August, where we talked about connectivity. And and warehouses, generally speaking, aren't set up for having low latency, you know, robust Wi Fi at every corner. And if the robots are going in every corner, they don't need Wi Fi to operate in every for every minute. Right? But in order for them to receive missions and tasks, call home, and stuff like that, they need they need robust connectivity. So that could be an issue too. So that's not necessarily the robot's fault. There are other factors at play. People, you know, your your network, other kinds of barriers, the missions you're sending them. Maybe you're not sending them the best best missions. Right? Maybe we need to rethink what missions you're sending sending them, and Ty talked about that already. Right? So it's a living and breathing thing. So, let's not just, you know, cast aspersions on the robot. It you know, no such thing as a bad robot. Right? It's it's a system that needs to be optimized. That's, I think the the main point here. Absolutely. Okay. Let's talk about people now. We've we've we've we've talked about the robots a little bit and headquarters and and whatnot. But when we're talking about scaling, and that's ultimately your goal. Right? We're we're we're we're transparent about it. We want customers to to deploy more robots. That's Ty. That's Ty's job. He wants to make he's into the happiness business, and he's in the happiness business so people could be more happy by by deploying more robots. So what are the what is it inhibiting them, from from progress, you know, in your in your worlds, Ty? Yeah. I think, honestly, it goes back to the comfortability with the technology. You have to trust the solution you paid for, you've brought in to do a job. And I understand that visiting many sites all over our different verticals, There is that risk that I know a human can get this done. They have they put humans on the job to back up the robots, which actually, in turn, slows it down. The robots aren't meeting the goals, the KPIs. But there's gotta be that trust of you are bringing in a very robust system, with support networks to ensure reliability to do the job that you're bringing it in or the robots in for. That's probably the biggest, killer to to progress is just that trust. And I I completely understand why the hesitation's there, but it is it is a really limiting factor that we have to overcome. Right. And and we have tools at our disposal, Ty's team being one of them, data, remote monitoring, on-site training, software updates that get the robots to be, you know, to do and be better. But, ultimately, there has to be a belief that that I'm going to redeploy my people to to new things. I'm going to give the robots the missions that they're that are make the work optimal. And, you know, I'm I'm going to optimize I'm gonna work closely with companies like Vecta to optimize the system for maximum, maximum performance. So just keep those in mind. Once again, we're Ty's here to help you look around corners. Right? Anybody can make a proof of concept work once or work for a short period of time. We're in it for the long game. Right? And and so so this is really about looking around corners. And, and in order to to really go around that corner, relieving some of those inhibitions are really an important part of Ty's job. Yes. Absolutely. Okay. Well, okay. The last one here. So this was an interesting one that Ty and I have been talking about for a month. It's nice to finally show it. There are and this was really insightful. This is organic. I didn't read this somewhere. It's not like, you know, I read a report on this. This was something that came out of Ty's everyday life. And I said, you know, Ty, how do you characterize the how the robots are working with with, with people on on the ground every day? What are you hearing? What do you see? And organically, this is exactly what you said. I just made it a little bit more brief, and I added some pictures. But these were the words that Ty used. So let's share these insights with everybody, Ty. What let's go through each of these robot worker interaction types first. So first one. Yeah. Absolutely. So first off, every company at least goes through the first two, the obstacle to the coworker. My team's goal is to get you through those stages as quick as possible into the optimizer region. But starting off obstacle, we see this usually right away. You introduce this technology, the robots into your warehousing, and they come into very well established processes. Mhmm. And there's always the competing factor. For workers who have done this process, they know it, and now a robot's in there. It operates a little bit different than what they've seen with manual drivers, and they clash. And it caused for delays at while that learning curve really happens. Yep. Then the next one is oh, go ahead. Hold on. And that so that's not just that's doesn't always have to be adversarial. We do see it adversarial. Right? Like like, drivers cutting the robots off or whatever. But it it's perceiving the robot as an obstacle to success. The outcome is clear there. Right? So we're talking about scaling operations. The outcome is suboptimal. Right? It's like you're getting negative value at that point. Right, Ty? Yes. You are. Okay. But that's why we have a success program. We don't just dump the robots at your site. Goodbye. We realize that these obstacles, as Ty said, are are natural in new particularly in new environments. And then we we're upfront about it. Hey. You know, there may be some concern. Let's win hearts and minds here. Get your workers to love the robots. Maybe even name them. Put a little name nameplate on them. And then they typically are operating in this middle category. So what is this category? What is it what do you mean by coworker? Yes. So coworker, we see this is probably a majority of where our sites are at right now. And this is there's acceptance of the robots. They know they're now part of the team, but they're not supplementing we're not into the point where robots are doing robot work and humans are doing human work. They're working together. They're in harmony. We're just not optimizing it. A good example I like to use of this is if you have a pickup location, thousand foot travel distance to interact staging for how it should be put into racking. In this scenario, you have your worker who's taking their vehicle, driving into the pickup area, picking up with the robots, bringing them back. They'll put their pallet away. The robot will drop at the end of the aisle. They'll pick that pile it up, put it away. So they are still seeing an improvement in their throughput, but we're not fully optimized. It's harmonious, but not as good as it could be. Yep. So and then the payoff pitch. Right? And this is to get to scale. I don't consider this a holy grail. I think this is the goal. Right? The goal of these programs is to and where the where the exponential value occurs is when you're looking at as the robot as an optimizer of your workers. Right? So, so let's let's talk about that briefly here, Ty. Yeah. No. I mean, we have a couple of sites that are in the optimizer freight phase. And once they finally cross that threshold, their you saw their throughput, their ROI, everything go up exponentially almost immediately. And what this would look like using that previous example I just said, imagine your manual worker who's doing the put away in the aisles. Instead of having to travel a thousand feet one way to pick a pallet and come back, They travel fifty to the end of the racking. Pallet's there. They put it away. They come back. There's two more there. Every time they turn around, you have pallets ready to be put away while the robots are just covering that entire distance. That's when you're in the robot doing robot work, humans doing human work. And Mhmm. That manual driver, their throughput has gone through the roof. You are putting pallets away left and right. You're just everything is exponentially better. Just really every aspect. It's very, very impressive and fun to watch when you have a site get into the optimizer region. Right. And that's where the scaling the scaling and, the real business value kicks in. Alright. So, I mean and this is sort of the vision here. Right? If I had a visual to describe, obviously, this is a little bit dramatic, But, but this is, this is the vision. So, thank you, Ty. Let me just wrap it up here. So I just wanted to remind everybody that, we have a very unique way of going from no bot to robot, if you will. Today, we talked a little bit about scale, but to get there, you have to start every journey begins with the first step. And we've got a very disciplined one, two, three, four, five, that gets you to scale. It's a it starts with, it starts with, you know, a discovery and then makes its way to to the scaling that we had discussed. So just wanna let you know that we, we, we have a very disciplined process to handle that. If you like this webinar or you want to watch this on recording, just go to vecton robotics dot com slash backslash webinars, or, go to our, go to the navigation at the top, click resources, and it's there. Clint on our team does a great job of providing fresh new content on LinkedIn. We almost had thirty thousand followers, which is great. So if you wanna get an understanding of to upcoming webinars or what we're talking about, what's in the what's in the, the news, stuff we're following, please follow us on LinkedIn, Instagram, as well. And our YouTube page is pretty robust these days too. So with that, Ty, first of all, I just wanted to thank you. Thank you so much for joining us, on on Robot versus Wild. Really appreciate it. Yeah. Thank you so much for having me. And then for anyone that has any questions about success and scaling or what my team does, please reach out. You have my email on the screen here. I'm more than happy to answer any questions anyone may have. Thank you again, Josh, for having me. Very good. Very good. Maybe we'll see you on another, another episode sometime soon, Ty. So thanks so much. So on behalf of Ty and Clint, who's on the back end of all this, and everybody else at Vectorn Robotics. Thank you for joining us, and we'll see you in August for our next our next episode of Robot versus Well. Have a great weekend, everybody. Bye. Thanks. Bye.