[Seth Patin 01:25] So, why are we suggesting that it’s time to automate differently? And what are we trying to cover in this webinar? We have over the course of the last, you know, what, 15-20 years warehouse automation has become a substantial topic of advancement. You know, software has been serving some purpose in that, but it’s changed substantially as technology has advanced. And so, with me today, I have John Stikes and Lance Anderson, who are part of Accelogix and LogistiVIEW. And we’re going to talk to you today about where we see the industry going and, and how we are trying to drive that path. We’ll start first with some introductions. For those of you who don’t know me, my name is Seth Patin, and I’m the CEO and founder of Accelogix and LogistiVIEW. I started my career at RedPrairie about 15 years ago, just over 15 years ago, and I’ve spent my entire career in warehouse software integrating to hundreds of different automation solutions, from you know, from the perspective mostly of a warehouse management system. Over the last nine years, Accelogix, has grown to become a leader in the implementation of warehouse software, and our largest practices in implementation of Blue Yonder, or formerly JDA or RedPrairie WMS. But throughout the course of my experience in WMS, I’ve seen a lot of gaps in how warehouse computer systems, warehouse management, you know, WMS, WCS, etc., interact with people, and I really don’t believe that, you know, the way that we’ve siloed humans from machines, and given people fairly limited quality of instructions and things like that. It just seemed like there was a better way to connect people to everything around them. And so, in 2014, I founded LogistiVIEW that we’ve developed into a leader in augmented reality, vision, mobility and warehouse connectivity technology. So also, with me, we have Lance Anderson, who’s the CEO of LogistiVIEW, Lance, go ahead, introduce yourself.

[Lance Anderson 03:30] Good afternoon, everyone. Hi, Lance Anderson. For those of you who don’t know me, I’m currently the CRO and VP of Market Development for LogistiVIEW and Accelogix. I spent 20 plus years in the logistics industry, mostly focused on people and process automation. With stops at Realtime Solutions, Beumer and Invata and a few other company trophies I collected along the way. The last four years, I was actually with Vuzix, which is a smart glasses, augmented reality smart glasses manufacturing provider. And that’s really where I had my aha moment that, you know, empowering the frontline worker with a new way to participate digitally, with smart glasses, augmented reality, platforms like that is a true game-changer for our industry. And that’s where I met Seth and came into LogistiVIEW where, you know, this is where the industry is going. And I’m excited to be part of the discussion.

[Seth Patin 04:27] Thanks, Lance. Also, with me, we have John Stikes, who is the VP of automation at Accelogix. John go and introduce yourself as well.

[John Stikes 04:37] Good afternoon. Glad to be here and speak with everybody. Like the rest of the panelists have been in the industry for about 15 years, with stops at Walmart for about 10 years running operations on the floor in a variety of settings across the way than running technical service and maintenance at another automation builder, how would one lambda industries and then Ran automation reengineering and reliability engineering contract with inside the Amazon network for North American Europe for their middle and last-mile buildings. And then most recently was the head of innovation in North and South America for DB Schenker, a global third-party logistics company, which is where I’m at Accelogix and LogistiVIEW in much like the rest of us, we had my aha moment, when I spent most of my career trying to figure out how to get technology to work with people and people to work with technology and automation. And the aha moment that maybe there’s a better way to do it. If we put people in the center of the automation, speed of peace, build processes to go into it, and then build our technology around it. I had the opportunity to come over and work with these guys.

[Seth Patin 05:45] Great. All right. Looking forward to having this conversation. Gentlemen, I’m certain we will have some interesting discussions here. We’ll start with, you know, going over, this is a four-part series. And so today we are on the first year, the first part in this series, focused specifically on why software is the future of warehouse automation, we’re going to go through over the next several weeks, you know, a couple of additional deep-dive sessions into various topics on this subject. And so, will continue to share those with all of you who attend, we look forward to having you join us for those sessions as well. And then, today, we’re going to start with a conversation about reframing automation. And so, you know, I mentioned earlier, most of you know, what warehouse automation is, or at least maybe you think you do, and what I’m going to start with is kind of challenging to say, is there a better way is warehouse automation. What we know today is that the only way and my argument in our argument collectively is that no warehouse automation is evolving. And siloed machines are no longer the best way to automate. Now, does that mean that machines are worthless and new, and they’re no longer useful? Not at all, we’re not suggesting that. What we are suggesting, though, is it’s time that we stop thinking of warehouse automation, from the perspective of steel bolted to a floor, that’s part of it, but there is there’s more to the story. And if the last, you know, what, eight months have taught us anything about the world, it’s that flexibility is more critical than ever, especially when it comes to building the ability to manage cost, and you know, and the ability to adjust to unexpected changes. And so when we talk about automation, and we talk about, you know, particularly, you know, to John’s point earlier, well, what is our strongest asset? Where are we you know, where are we most flexible? How can we, you know, how can we adapt, and, and, and optimize our business in the best way. The reality is that people and potentially autonomous machines that are flexible, mobile, and can respond to changing demands are also a critical part of the story. And so, when you talk about automation, you know, it really is necessary to start rethinking it with the perspective of connecting everything. And so, it’s not just about how fast can I chuck a box down a line? You know, that is obviously important. If you have such a, you know, such a conveyor system, you want to optimize its performance. But at the beginning of that system, how do you effectively put boxes onto that conveyor? How do you effectively move them off? If you don’t have a conveyor or you can’t afford a conveyor? How can you get the same results, or better results, more flexible results without ever having to go through that kind of expenditure? And in, you know, in really thinking hard about that subject, we’ve come to the realization that software in intelligent software that’s designed to orchestrate humans, robots, conveyors, sorters, artificial intelligence agents, and really also, technology that may not even exist yet, you know, software that or hardware that is still in the process of being invented. All of this needs to come together. And automation. And the strategy around automation can be focused instead of on specific machines, it can be focused around business objectives, and then the machines or the people or the process all become part of achieving a business objective. And so when we think about automation, we think that as we build smarter automation, we need to do it for a new kind of workforce, a digital workforce. And that digital workforce needs to be orchestrated with precision across humans, robots, machines, and artificial intelligence, and software needs to become the better connector. between humans and steel. And so as we, you know, as we’ve mentioned, the digital workforce, you know, especially in Lance’s experience over the last several years, kind of transitioning from fixed automation, and, and the and really the, you know, the being an early part of that industry and then getting into smart glasses, which is arguably the farthest forward way of, of interacting with a person. Let’s talk a little bit more about the digital workforce and how that impacts, you know, everything in automation.

[Lance Anderson 10:33] Sure, you know, obviously, as you said, near and dear to my heart, it really is the new digital workforce. So we define that as humans, plus robots plus AI, and maybe a little machine learning, really your asynchronous part of your operation. So, let’s, let’s start here with your workforce, right? Walk in any DC and right up on the wall, first thing you walk in, and you see is our people are our greatest asset. Right? And so, what do we do we hand those people a piece of paper with a bunch of skewed numbers on? We’re RF terminals that have a bunch of random computers speak complex exceptions, processes requiring lots of memory and, and repetition? All right, with the opportunity for error, that’s how we treat our most critical asset. Right. And frankly, this is why training and temp workforce is such a huge topic right now, because we’re providing our workers with such complex, complex process. All right, and what do we do next week, we decided, well, let’s help them out by putting up a big dashboard, and showing them in beautiful colors, how poorly they’re performing, right? So honestly, this is where we need to focus is on the human aspect. So, let’s all start there. And obviously, in recent years, we know we’ve had labor shortages in recent months, we don’t need to go there. But replacing workers, temp workers, workers shortages, or moving workers to different roles. With all the training and the learning, right, we need a way to communicate that’s much more natural, much more intuitive. So how do we solve this? We solve this with human-centric communications, right? intuitive, communication, simple and intuitive instructions. Am I in the right place? Do I have the right thing? And what do I do next? So, think about it in augmented reality with smart glasses. This is a red X over the wrong product and a green check over the right one. I don’t care what language you speak; I don’t care what your education level that makes sense. It’s very simple and intuitive. An arrow directing you instead of a location name, a picture of a product instead of a SKU number, and multimodal instructions, that includes visuals, audio, audio cues, whatever makes sense for the human being the way we interpret and act in the real world should be addressed into our operational, right. So why is this important because it allows us to digitize the human workforce, it allows them to meaningfully and immediately participate in this asynchronous automation to become part of it, right, not just executing directives, but by capturing data that we can now use in task optimization. Right? So, this human reasoning is very, very powerful. So, using human reasoning beyond the current ability of AI, being more diverse, and dexterous and robotics, and executing the work, humans really are your most flexible and valuable asset. So, you know, we’re not just about optimizing the worker, but we’re rather optimizing the human participation in the digital workforce in automation in software automation, you know, so how does this fit in with AI, it’s really about the worker being able to put inputs into our system to validate the data for AI that they’re participating in. So, this validation needs to happen at the point of work. It’s not about what happened, it’s about what’s happening. That’s how you get through optimization. with robots, robots and AI should augment the human and help the human, make them better, make them more accurate, and really compound and improve their total output. That’s the key. You know, so to frame this digital workforce in terms of software automation, you know, we connect and orchestrate the new digital workforce, again, which is robots, humans and AI into your existing systems and your existing fixed automation. This is really how we can deal with change. Right? So, fix automation is about consistency, right? Doing the same task over and over again, as fast and efficient as possible. Software automation, on the other hand, is really about leveraging change, the reality of change the flexibility to deal with change. You know, it’s no more it’s not about what do we do if things change? Now it’s what can we do when they change, right? planning for this, executing a system that has full change? So, we need to monitor and identify this through the human being what’s actually happening, then we need to redefine what we need to do next. Right. And it’s a little bit more about not what tests not just about what tests should we do, but how we should execute them together the how, and the what is how we get to true optimization. workflow optimization is really the end result here of software automation, and it’s across multiple points and point solutions can’t do this right. This is these have to be achieved over the entire organization, the pace of change in warehouses accelerating. And let’s be clear, a WMS and a WCS without this human element, right without this holistic view of what the desired business results are across a DC is not going to deliver the results clients are looking for. You know, and I can go on and on at this. But John, frankly, as a longtime end-user of this technology, I think you’re much better to explain this and where it ends.

[John Stikes 15:29] Yeah, thanks. Because I don’t think you could emphasize that point enough that when we start talking about the way we build technology, we built technology to be the most consistent and most efficient process in the warehouse. You’re absolutely right. But the problem is, is it does corral you into one way of working I mean, I remember back last year, taking a new hire out on the floor of a warehouse and hand them a scan gun, to see if they could figure out how to pick just using typical traditional process functions. And they looked at me and said, what’s a function key, they’ve never actually seen a function key. And in that workflow, you had to hit function three to say you picked an item and it, it blew their mind, we handed them a different device that was more intuitive. And they were picking with no instructions. And it was, it was really interesting to see. And, and quite frankly, I think about it, very much like we’ve seen consumer electronics change, and think about the phones. The example I like to use is automating is like we used to have cell phones, we had bag phones, if you wanted to update your bag phone, you get a new bag phone when you had just a regular traditional cell phone that it might almost text circa 2004. And you needed to update it, you threw it out, you got a new one, and your whole new system is up and running. That’s typically how we would automate here, when there was a new hardware feature that came out, it would include some software that did some different things. But you had to learn how to use that hardware better, which meant the human had to change their interface. Or the first time somebody handed me a phone, the Jedi hit the button, like four times to get a letter to show up to text about texting was one of the dumbest things I’ve ever heard of. And I didn’t want to do it because it’s too complicated. Now, with my smartphone, now I can text like a maniac. And we all do. I say that very much in the same way that warehouse automation and the digitizing of the workforce is happening, we’re no longer the hardware is making the humans change, we can put the software, which allows us to change the technology and make the technology work for us. It’s very similar to our smartphones, now, we all have smartphones, but they’re all architected a little bit different with what we have on them to operate appropriately for us. And I think that’s the change that we’re seeing in the marketplace. And that’s why the technology and automation in the software backbone is so important to have the right software that augments all these disparate pieces of the workflow to optimize it to run it in to make it capable for the humans.

[Seth Patin 17:59] So, John, that’s you know, you that’s a really interesting comparison, the whole, you know, the whole bag, phone versus you versus smartphone concept. You know, from the perspective of a, you know, maybe a more traditional WCS or WES, the software that we say runs warehouses today, you’re obviously under the WMS, which needs a WCS or WES, typically to interact with the fixed automation. You know, what’s the difference between those things and what we’re talking about now?

[John Stikes 18:29] I think it’s a fundamental shift in terms of the architecture when you look at a WMS, it is built to, to make the best shuttle system around or the best. Pick what type of fixed automation piece, it is designed to make that the most efficient. But what those systems tend to forget is where the real point of work happens, where the real value is created, is where the human interacts with the product to either do the value-added service, to do the pic in the verification to do the processing of that product. That’s the point where value is created because that’s typically the more complicated piece of the system, the stability, more complicated process that has to be managed. Therefore, your workflow optimization when it’s just about how to move product around leaves the biggest piece of optimizing potential on the floor, undone, and that’s, that’s working with people. Because robotics is great, as great. The technology is great, and it’s growing quickly. But still, the most complicated functions are handled by humans. And they are the least automated portion of that and workflow optimization of that process. And it’s quite frankly, just a big gap there. You can’t automate, thinking you’re going to make the machine better and forget the humans are there. And in point of fact, you got to start with the humans and then make the machine reflect what the humans need you to do. That’s the correct way to automate.

[Seth Patin 19:52] Right. So basically, the difference here is what we’re saying is that software automation starts with the people in the process. Then ends with the technology, whereas historically we’ve gone the other way.

[John Stikes 20:05] Yeah, we always I mean, I can remember doing design studies for years where we looked at the process load and we wanted to say, How big are the boxes are each picker the case picker, the pallet movement, and then we would figure out okay, well, this type of sorter, if it’s a large like case, pig driven business, this type of sorter is going to run better because of these are your sore points, this is your batching process. This is the throughput need, you have the facility. And then we asked people to go stand in the middle of a module where big giant stack of labels and pick up heavy boxes and put them on a conveyor belt, and then walk back and forth across the building all day to do that, versus if we automated it, where the humans were first, to figure out what makes that job the most efficient and the most process compliant, and the easiest for the humans to be efficient. And then we would probably start to layer in different type technologies like we’re seeing today. With flexible automation coming into the case pick environment and or in a real a meaningful way, in the Amr and STV space in a really meaningful way we would automate much differently versus building a faster sorter, because that’s not necessarily where the true cost of your facility is. Sure, humans in the facility or 80% of your calls, why wouldn’t you make them the most efficient as possible?

[Seth Patin 21:20] Right, and if you can’t get, you know, if you can get, you know, 30,000 cases a day out of your sorter, but you can only get 3000 cases a day into your sorter there. That’s Yeah, that’s, that’s a bottleneck that just doesn’t work. So, you know, if this is a new software platform, you know, new a new system, where does it fit into our existing technology landscape? I mean, how do we, you know, how do we connect all of the, you know, all of the existing systems, to all of the new technology that we talked about, you know, AMR, or, you know, smart glasses and things like that. I mean, this is really, it sounds like we need, you know, that this really is a whole new layer of technology inside the warehouse.

[John Stikes 22:06] It has to be. I think there’s a lot of people who are trying to have that one system that does everything and that whole fantasy of technology, which is a cool idea. But that also sounds a lot like the Titanic where they forget to put enough lifeboats on it, when you make something that is that complicated and has to deal with that much change and that much process optimization, you start to so complicate the technology that then the technology can get out of its own way. I think you’re absolutely right. So we’ve got to have a different layer, which is that middle layer, and it’s a translation on a workflow layer, where it sits between the Ws which do a great job of talking to the RP systems and in the systems that are already integrated with w Ms. In this middleware layer, they can talk to the various execution software that’s there for the fixed automation because it does a great job of running shuttle systems, not a great job of running people. But you need a system that can also talk to the people and also talk to the other robotics. In the bigger piece, I think what we’re seeing is the rate of change. So, you need that middleware layer so that you can start to unplug automation, when it doesn’t make sense anymore, and plug it back in when it makes sense. And vice versa. I think that’s really the future-proofing, if you will,

[Seth Patin 23:19] Right. And they I mean, I think I think when you get that, you know that connectivity layer, you know, you when you start to optimize across everything connected with visibility, then you can finally start to optimize holistically for overall business performance, rather than just focusing on the throughput of lines per hour. You know, that that that is, I see a lot of companies and a lot of our customers have challenges where they have one part of their business that’s super-efficient. And then it bottlenecks, you know, the next part of the of the operation, and then we ended up kind of playing, you know, it is kind of like whack a mole, where you solve one problem, it creates another problem.

[John Stikes 24:00] Absolutely. And I think that’s the biggest challenge we’re finding is that our traditional way of automating, we’re gonna create work in progress points and buffers throughout the facility, as various rates of operation are different in different functions of the warehouse. Well, to your point, if you optimize your order filling process, but don’t optimize your shipping process, you end up with a bottleneck somewhere a bunch of problems with throughput. And I think it’s really true when you start looking at the software, I mean, think about the software agent, as we’re all used to. In a traditional salt sorter-based throughput system. There’s really good agent how’s it how many cameras or how many boxes are going under a camera every x number of seconds and what the distance is between them and what your reads are, and what your heart rate is, but they don’t really tell you the level of effort it took to put those cases onto a conveyor belt and get it up to your sorter. And really that’s the point of work. Right? Speed and efficiency are different.

[Seth Patin 25:04] Yeah. So, and that’s a that’s a really interesting point. I mean, so and speed is an interesting concept because speed at speed is a factor really across the board. And efficiency is a factor across the board, not just in how fast something moves in a straight line, but how fast things can adapt and react. And so if you start talking about, you know, putting in a system like this, a layer like this to help connect all of these disconnected dots, you know, how do you Where do you start there? I mean, how is deploying this kind of technology different than deploying a sorter, for example, or some other large fixed automation project?

[John Stikes 25:46] I like the statement, the military uses a lot fast is smooth and smooth is fast. And that’s the point of reference in the beginning, when you look at how you bring this in, as you want to look at how do you have a smooth process flow, from the time a trailer comes onto your yard to the time it leaves your yard. So that is the product is just smoothly moving through the facility. So what you have to do, you have to look at it holistically, you have to look at the fact that I might need to slow down one function of my warehouse to speed up another function of my warehouse because the overall aggregate process change makes me more efficient overall. And I think what that really starts from is you got to know what success looks like. And I think that’s the hard conversation has to be had before you do anything with automation is what is right look like what does success look like? Because otherwise, and this, unfortunately, in a lot of automation concepts is a problem. We don’t always have the same definition of success, we’ll have a conversation, we all think we’re playing football, to use a sports analogy. But sometimes it’s European football, and sometimes it’s American football, we don’t know how to put points on the board. Because if you’re talking to a point solution provider, they may be talking about, you’re going to save a whole bunch of money by putting in this sorter, or this Amr this robotic system or this, whatever it is. But they’re not telling or may not have visibility in line of sight into what else they will be costing you money in, because they need to any change you make is going to create upstream problems and downstream problems. So that holistic look must be factored in first.

[Seth Patin 27:22] Right? And I think too, when you look at, you know, when you look at what is the definition of success, I think one of the challenges that most companies get into with automation projects, and certainly our customers get into these challenges on a regular basis, on the extra logic side, is you’re trying to build, you know, a solution that takes three years to design and another year to implement. And you’ve got to guesstimate what’s going to happen, you know, 5678 years in the future and hope that your crystal ball was pretty darn accurate. And so, you know, I how I think I think part of the part of the conversation, too, is how can we build a solution that fits the Cato fits now, but is flexible enough to move, you know, to actually respond in the future and grow with the business? Quickly? I think

[John Stikes 28:07] I think you’ve got the that’s the exact right question that is. So when you look at replacing a W m s as a long-term, project that takes a lot of time, that’s a lot of effort, there’s a lot of risk, they’re putting in new fixed automation can take years to do that. That is difficult. So what do you have to do is have to be able to break it up so that you can incrementally adjust up and down the, the automation scale as the business changes, because there’s both macro and micro trends that you have to adjust to. Typically, when you’re doing fixed automation, you’re going to look out three or four years in terms of what your projections are, quite honestly, do any of us have real clear business projections of what 2021 is going to look like? Granted, 2020 has been a bit challenging, let’s say. However, though, in many cases, even the small things do you understand as a business, that’s the switch from Pallet movement to case movement to each movement, because in certain businesses, it’s moving one way and in other ways. And that’s very cyclical, even with the economy. When we start to see recessions, we start to see the lower order quantity size, which are largely driven by factors outside of your supply chain and outside of our ability to forecast. How do we automate so that we can do that going up and down the channel? And the only way you can do that is by building a software layer. That’s robust enough so that as you change, you don’t have to change everything. It’s we want to get away from throwing the baby out with the bathwater, which is where we do fix automation.

[Seth Patin 29:38] Right now. I think that’s a really good point. You know, Lance, as you know, what do you what are your thoughts on all this as we talk about the operational impact? I mean, from a technology perspective, how do we respond to this

[Lance Anderson 30:02] Sorry guys, muting there have been chomping at the bit to jump back in, I got so excited to start, you know, so I look, I boil it down like this, I mean, the value is turning the enablement back to the client, right. So with this platform in between connected, you know, with a single connection to your legacy data systems, now you can connect to it and drive up a workflow for your humans, you can connect to robotics companies, vendor agnostic, you don’t have to choose one single robotics company, you can choose many, whatever works for you. Any type of automation, you can choose to do human workflow optimization, you can connect to technologies such as smart glasses and augmented reality. That’s the value. The flexibility is there for the client in that agnostic approach. You’re technology agnostic, you’re vendor agnostic, you have control of your workflows. And those that change to your workflow happens through your people, your experts who know your business, you don’t have to go back and write a big s o w and pay a big check to someone else to do it for you. For three, pls think about the ability to change your process. Anytime you get a new client simply on your own without a huge lift, and but still have everybody participating in this digital workforce, partners and vendors take your solution to fill gaps with human processes, smooth peaks, with human processes done through workflow enablement. So, I think the value prop is there. For the end-users. I think this type of software automation can really bring everything together and drive real ROI for a lot of different participants in this in this entire puzzle.

[John Stikes 31:37] Man, that’s a great point. I mean, what other way can you pull the institutional knowledge that people have out? When we write code for fixed automation, it loses the institutional knowledge. And I’ll give you an example I was doing a project with some folks and wondered why the middle of the month, people would move toilet paper with smaller pack sizes, to the front of the building to start order filling smaller packs as toilet paper. And then the beginning of the month, they bring the big packs of toilet paper down. That’s when the order fillers one day said, why are you doing that? Because you’re picking it out of order. He said, Oh, yeah, the first of the month and the 15th of the month, we ship big packs of toilet paper all the time. On the off weeks, we ship little packs of toilet paper all the time. So, it’s just easier for us to do this. Our systems never picked up that nuance. And it was really interesting to see that the guy on the floor, who is doing the job all day, every day figured out something that all of our fancy technology completely missed. And if you don’t have a software automation strategy can augment support and pick up those nuances. You’re leaving a lot on the table.

[Seth Patin 32:42] Yeah, absolutely. I mean, that’s there’s definitely seen, seen where the industry is going and really seeing where the world is going. I think, you know, we’ve all come to the conclusion. And I think many of our many, many other folks in the industry have that have done so as well. Change is not a matter of if it’s a matter of when and it is actually a matter of constant it is always happening. And again, the last eight months has just been you know, basically a kick in the shorts for all of us to remind us that hey, by the way, the world still has control over itself. And it doesn’t matter how well you plan, you know, it’s probably not going to it’s not going to work out perfectly. And so, you know, what we try to do with, you know, with this concept is how can we build an automation strategy that allows you to respond flexibly to, you know, to all of those various changes in the business, and then also leverage that asset of your people in a way that is actually connected to the automation that you have in the building? Again, it’s, it’s not even, it’s not about even what type of automation is, you know, is in the building, it’s actually about what type of automation should be in the building? what options are available, and what can you do about it in a way that is effective for your business. So, with that, we’re going to move into a quick closeout here and jump into Q&A briefly after this. But what first Firstly, I’ll quick do our you know, my little pitch I got it, I got to say something here. So Accelogix, obviously, as a consulting firm, and as experts in, you know, in warehouse management technology over the last, you know, the last decade or so, we’ve become very, very attuned to the challenges that our customers have in this space. And we’ve been focusing on building up, you know, consulting capabilities in automation, and particularly, you know, leveraging John’s perspective in, you know, in talking to folks about how they might be able to change their automation strategy or enhance it or evolve it. And so, you know, we offer a free conference or conversation with John, John, can you quit, you know, give a 22nd overview of what it is that you asked me Want to hear from folks on these quick times types of questions?

[John Stikes 35:04] And the big things we’re looking for is just like we talked about earlier, do we understand what right looks like? Do we understand this scale and magnitude of the operations and what we hope it’s going to grow into, and really have an open conversation about those factors that are going to lead us down the right path, because it is an iterative approach. And that’s the big piece in the early conversations is understanding that automation today is not a five- or 10-year decision, it should be an iterative, incremental approach to the process.

[Seth Patin 35:34] As absolutely, that’s, that’s a great way to put it, you know, iterative value, let’s get value one step at a time. And then let’s find a way to build cumulative value over the course of time without having to wait for an all or nothing type of strategy. also put a quick plug for, you know, Section two, phase two of our webinar series here as well. You know, on the 22nd of October, which I believe is two weeks from now, we’re going to go into more depth about a human-centered, human-centric approach to automation success, I look forward to you joining and, and discussing with these guys again, in a couple weeks. So, with that, the prepared portion of this, you know, this presentation is, you know, is coming to conclusion. Thank you, for those of you who have joined, we appreciate your time, and we look forward to answering some questions here. And so, I’m going to go ahead and pull up some questions that we have in the list. And, you know, begin, begin doing some Q&A here. So, see here. So, there’s a couple of I’m in a few simple ones first. So there’s one here that as you know, as I decide which questions or list which questions we’re going to answer, you’re going to see the questions that we’re answering show up on your Q&A screen as well. But the first one here is, is this automation initially focused on JD AWS customers only before expanding to other WMS vendors in the market. And given the fact that x illogic has a strong background in BY or JDA WMS, that seems like a logical question. The answer is, no, it’s not focused on JD AWS customers, it’s the LogistiVIEW platform was built from the ground up with WMS agnostic integration as part of the initial plan. And so we actually have customers, you know, with JD AWS, but we also have customers with Highjump, w, MS and running legacy, you know, man, or, you know, homegrown systems. So no, there’s no real requirement to have blue yonder BMS or something like that. So that’s a good question, and one that we can, you know, quickly, you know, quickly take care of. So, one other question here that just came in is, when you talk about connecting workers, how do you, you know, how do you do that? And what’s different about that than what other companies have done? And so, I’ll quickly start this, I think John is probably going to have an even better perspective on this. When we talk about connecting workers, and you know, and doing it in a different way. The primary difference is the difference between viewing mobility as data, versus viewing mobility as human interaction. You know, if you think about a traditional voice system, for example, it’s a transaction. Hey, go here. Yep, I did it. Hey, you know, grab this. Yep, I did it. The system isn’t attempting to imply any intelligence, and it’s not collecting enough data to validate or help the worker make a better decision. And so when we start talking about how do we connect workers differently, it really starts with very, three simple questions that the system tries to help them proactively help them through basic artificial intelligence answer three questions. Am I in the right place? Do I have the right stuff? And what do I do next? Almost every frontline process can be broken down into repetitive, you know, repetitive, you know, versions of those three simple questions. And so we have John from a floor perspective, you know, you’ve seen how users interact with our software, and, you know, and it from an operational perspective, what’s your take on that?

[John Stikes 39:34] I’ve told Seth a few times that in our past life, maybe I shouldn’t be proud of it, but I kind of am. We get a lot of whiz-bang systems from some yahoo over in Silicon Valley that was really fancy and cool, and all this other stuff, but they made it so complicated. It just wasn’t worthwhile of using in, in the warehouse because they tried to get all the data in the whole wide world together to try to make better decisions. And when really, you need something that’s pretty straight. And pretty simple and augments with the people are doing. And so, from my experience, it’s one of the things that the logistics platform did really well. And quite honestly, I was skeptical The first time I used it so and pulled a clerk out of the office who’d never, I don’t know that she’d ever been on the floor before and handed her a device and said, go to town. And she could follow the workflow. She could follow the plan. She understood the three questions, what they were asking how they needed to progress forward. So I think that’s a long-winded answer to say, I think the approach here is that we understand that at the end of the day, it has to be simple enough to be consumed and useful to the end worker, and we build out from there.

[Seth Patin 40:45] Alright, thanks, John. We just got another, or we just got a great question. You know, how do you address information security concerns with legacy automation systems control layers, as you move to the digital workforce, I’ll jump in on that one. Tech is your tech is, is kind of my baby here. Yeah, information security is probably if optimizing humans is the most critical thing in a warehouse or the most challenging thing in a warehouse, I think keeping the data that we use to optimize them safe is probably the second most challenging. From an information security perspective, a lot of it has to do with the capabilities of the legacy systems and determining where you, you know, what paths you have to, you have to take from a data transfer perspective to ensure that data is moving in a, you know, in a secured manner. So, in the case of LogistiVIEW, the way we handle this, inside the walls of LogistiVIEW is the devices themselves. And all communications between devices and external systems are generally secured via encryption. And so there are obviously, you know, if it’s, if it’s inside the customer’s firewall, they may choose to not do that, because no one would hope that inside their firewall things are, you know, things are relatively secure. But certainly, when we’re deploying in the cloud, every single communication of any kind is encrypted. And it is, you know, if it’s coming from a third party system, it’s using some sort of standardized, you know, a protocol such as JWT, for any of you tech guys out there. But it’s, it’s really about, it’s really about understanding what’s already in place because the Brownfield scenario is a challenge. If you have a modern WMS that can handle you know, modern, you know, https web service calls, then that’s a really great way to make things, you know, pretty straightforward. If you have a more legacy WMS, that maybe only has the ability to do nonencrypted file transfer, then you have to build kind of silos, so to speak security silos around those communications. And we do that fairly effectively. With a number of different scenarios, we do File Transfer securely over the internet, you know, we do web service securely over the Internet, and obviously, you know, inside a customer’s network, every information security team has a different set of requirements around what data does and doesn’t get encrypted, and how you know, and how. So, our objective is to support any and all of those different scenarios. And trust me, there are many, many different scenarios. So, unfortunately, there’s no one size fits all solution. What I do know is that we haven’t find an answer every time. And I think that’s the key here is if the software is designed in the right way, kind of taking into account modern security threats. And you know, and by modern, I mean, like every new evolving security threat that shows up every other day, you know, we just have to stay on top of that, and work with our customers and their information security teams to do the same. So that’s a great question. Thank you.

[Seth Patin 43:57] Oh, here’s an interesting one, how would this kind of system integrate with my labor management software? And you know, and what would it add? From a, from a technology perspective, it would integrate with labor management software the same way, you know, the same way that, you know, most any other system would integrate using, you know, using the logical transfer of, you know, of data, event data, you know, scan data, what have you. But from a from an operational perspective, the data can be used in a very different way. And John has a little bit of experience using the data from LogistiVIEW in a slightly different way to provide visibility to new things. And so, John, what are your thoughts there?

[John Stikes 44:36] I think it’s the question about LMS is to wet it, if you’re looking at it from a management viewpoint or a holistic kind of a corporate viewpoint. That’s right, it can integrate back into what you’re currently doing. However, I like to know why we’re doing something a facility and labor management exists to let operators know how they’re performing against a standard and help them to get better, basically the whole idea what you measure matters. To me when we start talking about what can the platform do for you, in many cases, when we looked for deployment opportunities, there wasn’t a real need for a massively complicated or are bigger LMS function, because at the end of the day, the end user could see what their performance was. And honestly, as a company, that’s all I care about, I cared that my workers knew how they were doing, how they’re performing its goal and that they were getting better every day. And the big part was, is because of the dynamic nature of this system, there existed a process to where we could understand what the labor management standards should be by what’s happening, not by what we got, with a stopwatch one time a year doing a time study, five years ago, we actually got real lab data that we could work with to understand better ways to process I mean, when we start talking about these kind of systems and reporting structure, I kind of laugh to myself that when you go out to do Labor Management Studies to build an LMS how many of us drive the speed limit? When you see a cop on the side of the road? We all do we do it right? We put our blinker on, you put the phone down, whatever you’re supposed to do you do the process, right. You don’t always do that when you’re out operating and just driving your car. The platform here gives us the ability to see real-time what the standard should be based on the process at hand and start to make tweaks to make the process better.

[Seth Patin 46:39] It’s a great way of putting it. Thanks, John. Let’s see here. There’s a couple of questions here set that I think related.

[Lance Anderson 46:48] If I’ve been 10-year-old if I have a 10-year-old ERP system with basic inventory, but no tasking. Could I use your platform as opposed to buying a costly WMS? that goes along with another question here that, you know, we’re a midsize e-commerce shop? I’m not really ready for robots. How can we use automation, you know, for pick pack and ship? This type of client in this type of situation, that’s really exactly what the legendary platform is built for. Right to slowly move your way into automation in a way that you can afford, and in a way that justifies fixing a process within your facility. So you don’t need a full WMS to do a task, we can come in, put in that testing layer and help you perform better until such time as you’re ready to take advantage of the things that are brand new WMS can offer or as a midsize e-commerce shop, right? Yep, you’re not ready for robots. So, don’t deploy robots, right? Let’s look at your processes. Let’s give your workers smart glasses. Or let’s give your workers a simple cell phone that we use to drive data capture and process instructions. It really doesn’t matter; you can start small with this platform. But once the platform is in, then you have the ability to add a robot when the times ready or add another process or add a new technology that frankly, we haven’t even seen yet. And the third question is this can grab is, you know, do you typically recommend changing one process or looking at everything holistically. We do like to have a holistic view of where you are and where you want to go. But most of our clients start with fixing one individual process. And that’s how they start with this. That’s how they get the platform into their facility. And what happens next is they start to fix lots of other little processes, ones that you couldn’t justify buying a brand-new system and a whole new interface to just to do. But once you have this platform in, you can start picking off the processes on your own and enabling your operations folks to really start improving their processes without spending a lot of money.

[Seth Patin 48:47] Right? That’s a really valid point. I mean, I think one of the challenges a lot of folks face and probably one of the reasons that bad processes or sub-optimized processes stay, you know, as prevalent as they do for as long as they do is because fixing them and you know, Filling in the gap or you know, or whatever it happens to be is just too much work or too expensive to do. And if you come at it from the perspective of, again, iterative improvement, you’re not trying to bite off more than you can chew not trying to you’re not trying to plan for something that there’s just no way you actually know what’s going to happen. But instead focus on, you know, improvement day by day, you know, process by process and then keep on connecting the dots. It’s when you start connecting all the dots that the holistic orchestration becomes a real game-changer. And, you know, we’ve, we see that with our you know, with our customers who start small and then go to another use case within the same you know, within the same building and or even another use case within you know, the same network in the case of a three PL So, great, you know, great questions and, and great answer. So, let’s see here looking at a couple of things we are at 1252. What we’re going to do is we’re going to keep on answering questions. We’ve got a, you know, a pile of them. Until right at one, and anyone who submitted, you know, any direct questions, we will follow up with you after, you know, after the event as well.

[Seth Patin 50:15] What data points are collected to improve processes over time? And what do you use for analytics? That’s a great question. So, we have, we have a workflow model, a workflow engine that drives the entire process and drives every single process and LogistiVIEW. And this is actually part of what makes LogistiVIEW a different product than what you typically see, you know, in AWS, when you start from the perspective of saying, I’m going to design a process for an asset in the workforce, whether that be a human, a robot, you know, an artificial intelligence, you know, agent, what have you, you have to have a standardized model, across which all that can be applied. And that’s where we, that’s where we built this workflow engine as the starting point for everything. The great thing about that is as any member of the workforce, again, the entire digital workforce, human-robotic, you know, Ai, as any member of the workforce interacts with, you know, with a task assignment, or with other, you know, asset models, or inventory models, or what have you, as any of those, you know, as any of those activities take place, we record every single step of the workflow that we configured to define the process that this interview that this particular workforce member was going to take. What that does is that gives us the ability to see the interaction, the timing of every single transition from one step to the next from one data capture to the next, all of that gets logged into what is in essence, a very, very detailed transaction log, sometimes we capture a lot more data than most companies would ever actually need to use. But in doing so, it gives us the ability to post analyze, as John mentioned earlier, you know, the actual performance, as well as you know, standardize or evaluate, you know, evaluate the, you know, the variations, and, you know, and gain insights on what a reasonable standard can and should be based on variations in performance. So, you know, from an analytics perspective, we have, you know, we have a substantial amount of data that we can use to drive decision making. And that’s, you know, that that workflow data that is standardized across every single asset that is, you know, every single workforce member that’s working in the building, is what, you know, what starts is the baseline for our ability to analyze and provide, you know, provide kind of previously invisible insights, because we just did not have that level of information from the floor. It’s not about what was done. The w mess is pretty good at figuring out what was done. The better question is, how was it done? And that’s where LogistiVIEW has visibility to how that a W mess does not have. And that you know, that WES, or WCS does not typically have either, it’s the question of answering not just what was done, but how was it done, and then being able to go back and say, Okay, this could be done differently, and produce a better outcome. So, let’s change how it gets done. Not necessarily just changing what should be done. So that’s another great question.

[Seth Patin 53:35] Lance, and, John, is there anything here that I’m missing?

[Lance Anderson 53:37] The top, though, there are a few questions that are, I think, probably can’t be addressed here. How do I assess my current state when I have multiple systems? Do you make recommendations on warehouse layout to optimize short term? Can you give me an estimated or compared ROI for a variety of options? for those folks who asked those questions, I really think, you know, sign up with John for 15-minute conversation, so we can actually understand your uniqueness. This is not a one size fits all, it is the complete opposite of one size fits all. So, without understanding what you’re trying to achieve, what your warehouse looks like, what you’re handling, whatever, we couldn’t, couldn’t really answer those questions. So, I think for those folks, it’s best to give another 15 minutes at another day and sign up with John, it was on the station.

[Seth Patin 54:18] I do think I see one here that, you know, we’ve got only a couple minutes left Lance, but I think we do have, we did have some partners or potential partners who signed up, you know, to be on the session as well. So, one of the questions is, you know, do you sell machines direct? Or do you work with specific partners? I think really, more broadly, the, you know, I’m going to expand that question to discuss in general, you do we implement with partners do we sell with partners, etc. And, you know, I’d like you to kind of cover that Lance quick as the last question we answer.

[Lance Anderson 54:47] Sure. The answer is, absolutely. We work with partners. We prefer that you’re the expert on your machine. We’re the experts on the operations and we work together. We don’t necessarily sell the machines direct. Predominantly, we do not. We do smart glasses, things like that. But bigger automation, we want to work with partners, because it’s the entire solution that delivers the value to the client. And we are not here to say we take everything over where they were, we are not the one size fits all. Again, it’s not about selecting a vendor that does everything. It’s getting a platform that does anything. And that’s really where we come in.

[Seth Patin 55:22] Yep, absolutely. Very, very well stated, Lance. I mean, that was a great question. And I think probably the last question that we can take, we are at 12:58 here. And it does look like see here, it does look like we have managed to have a number of folks stay with us all the way to the end. So, thank you very much to the folks who are still with us on the webinar. As Lance said, please reach out to you know, to answer any more questions that you might have. We love, you know, we love talking about how things could be better. It’s just kind of what makes us tick. We enjoy it. And so, thank you for the time. Thank you for listening to us asking questions, and we look forward to talking to you in the very near future. So, with that, we will go ahead and close the webinar. We look forward to seeing you in another couple of weeks for number two. Thank you