Andy Williams: 0:03

if I have the most automated robotic systems that are available today, I'm able to store a much denser selection of SKUs, more inventory days on hand in a smaller space, I'm able to get a much higher performance level, overall throughput out of that smaller space than I ever could with a manual operation, just not possible.

Tom Raftery: 0:33

Good morning, good afternoon, or good evening, wherever you are in the world. This is the Digital Supply Chain podcast, the number one podcast focusing on the digitization of supply chain, and I'm your host, Tom Raftery. Hi everyone and welcome to episode 343 of the Digital Supply Chain Podcast. My name is Tom Raftery and I'm excited to be here with you today, sharing the latest insights and trends in supply chain. Before we start, I'd like to take a quick moment to express my gratitude to all of our amazing supporters. Your support has been instrumental in keeping this podcast going and I'm truly grateful for each and every one of you. If you're not already a supporter, I'd like to encourage you to consider joining our community of like minded individuals who are passionate about supply chain. Supporting the podcast is easy and affordable, with options starting as low as just three euros or dollars a month. That's less than the cost of a cup of coffee, and your support will make a huge difference in keeping this show going strong. To become a supporter, simply click on the support link in the show notes of this or any episode or visit tinyurl. com slash dscpod. Now, without further ado, I'd like to introduce my special guest today, Andy. Andy, welcome to the podcast. Would you like to introduce yourself?

Andy Williams: 1:50

Tom, thank you for having me. Yes. My name is Andy Williams. I am the executive vice president of sales for ExoTec in North America. ExoTec is a leading warehouse robotics and software provider.

Tom Raftery: 2:07

Okay. And what kind of robotics and software are you selling?

Andy Williams: 2:16

Yeah, a few main types. Our flagship hardware product is called our Skypod system, which is a robotic AMR or, you know, automated vehicle that can, go inside racks, retrieve storage bins, cartons, and then exit the rack on its own and bring those items to either a, an operator or another robot to do piece picking or a robotic dispatch to, you know, conveyor or pallet.

Tom Raftery: 2:54

Okay. And you said software as well?

Andy Williams: 2:57

Yeah, software is a major component of it all. Certainly you know, probably the hardest part. So orchestrating the flow of goods, managing inventory deciding which robot should take the next mission, how it should take that next mission, what's the most efficient way for the robot to go. How do you meet the different priorities that you might have associated with an order or group of orders in terms of sequencing or cut off times, et cetera, et cetera. It's all driven by software. And that's really the biggest and most critical component to getting the performance you hope to get out of one of these types of systems.

Tom Raftery: 3:41

Okay. And I gotta think that the decision for an organization to purchase, I doubt any organization is going to purchase a single robot. So it's probably a fleet of robots and software. I'm suspecting that that decision is going to be very much kind of a cost benefit analysis because robotic systems, robots and software, decision don't come cheap. But we're in a world of inflation as well. Rising costs. So how are you seeing companies make that decision between hiring more staff versus increasing levels of automation?

Andy Williams: 4:25

Great question. Historically, in this business, it really has been an ROI calculation. So Hey, if I'm to continue as I am now with my manual staff, manual operations, I can achieve X you know, if I add a completely automated warehouse robotic system, maybe I can achieve Y. There's a cost associated to all that. Let me run the figures and see what we want to do. Of course, the labor shortage is a very real thing. And has impacted that calculus to a great degree. So in the current environment, you know, it's looked at a little bit differently because many times you just simply can't find the people to do the work. And in addition to that, I, I think that bucket of issues has become somewhat table stakes, you know, in other words for, for these companies considering to automate. So yes, there should be some sort of reasonable ROI period you know, less than three, three years. It also addresses the labor issues, but the other and, and perhaps more impactful part of that decision making process is what can these systems do in the supply chain. And if you have a node in your supply chain, whether it be a parts warehouse at a manufacturing location or a distribution center, if I have the most automated robotic systems that are available today, I'm able to store a much denser selection of SKUs, more inventory days on hand in a smaller space, I'm able to, get a much higher performance level, overall throughput out of that smaller space than I ever could with a manual operation, just not possible. And when I start thinking about ways to transform the supply chain by, you know, for example, if I'm a CPG company, being able to do all those things I just mentioned and be able to sequence items by line in a carton. In a certain order on a pallet, and then also those pallets in a certain order off in reverse stop sequence for a delivery route, you can see that there are many impacts outside of the warehouse as well. And so we talk frequently about supply chain transformation. And one of the fundamental tenets of our belief system is maybe you can transform your supply chain using this orchestration engine and be able to locate warehouses closer to customers, closer to manufacturers, achieve later cut off times, better service levels you're able to impact the performance of employees in store lives easier, having fewer damages and, you know, in terms of digital supply chain, have a lot more information as well to manage inventory levels more effectively, lower the different types of you know, whiplashes that we have traditionally seen between these different nodes of supply chain.

Tom Raftery: 7:46

Yeah, and talk to me a little bit more about that, because I'm interested to learn a little more about what robots can do in a warehouse environment that people can't. I mean, obviously it's the things like they don't need to take breaks. They can work 24 seven if necessary. You know, they probably have to go and charge for half an hour or an hour or something. But let's say 23 hours a day or whatever it is. But there's a slew of other things that you mentioned in passing there that robots can do that, you know, it would be a lot harder for people to do. You talked about density of racks and things like that. So go into a little more detail about that. And obviously we're not talking about it replacing people because these robots have to work in conjunction with people rather than instead of people, but it's just that they're making people more efficient or more, yeah, more efficient, able to move more stuff in the same amount of time, right?

Andy Williams: 8:41

Yeah, yeah. Well, you can imagine a situation where let's say I'm a large CPG manufacturer and one of my main product lines are chips. Baggies of chips that would go into a convenience store and, I've determined that it's of great benefit to those individuals at the convenience store helps me get more business. It's a, it's a nice value added service that they like, if I can deliver those chips in a very specific sequence, according to the way they have those chips laid out in their store. It makes their lives easier. It helps them get more sales being able to deliver, you know, a one quantity of one or two versus a case lets them be more efficient with the way they manage their inventory. So what that could mean inside the warehouse is that I would need to, as a picker in a traditional world, walk all over the warehouse, grab one of this item, one of this item, one of this item. Not only have a very slow pick performance and rate compared to a goods to person robotic system, but then have a very difficult process of arranging those in a case in a very specific way. Right. And now with robotics just as an example, all of that can be automated. So the software can determine, you know, not only the order characteristics when it needs to be ready. But it can also say, Hey you know, here is the, the aisle layout of the store. Here is the preferred sequence from that store owner and bring all of the items to the person or the robot in the exact sequence needed without them having to even mentally process that part. So, It allows for some big productivity and capability enhancements that simply weren't possible before.

Tom Raftery: 10:39

Okay. And you mentioned in passing as well, the fact that with robots, you get a lot more data. Can you talk a little bit about what kind of data you can get from robots and how that can help organizations, you know, achieve their goals better?

Andy Williams: 10:56

Yeah, absolutely. So, you know, data is literally everywhere in these systems. You know, if you just think about from the receiving process, you know, we can automatically receive products, make sure that we're immediately, you know, scanning the barcodes capturing any information that might be associated with LIFO or FIFO. Correctly matching them against the inventory. So a lot better accuracy and already creating a much broader perspective on what can be accomplished with inventory. In many times in the past, there were these push flows coming in and there just wasn't 100% inventory visibility and, you know, you end up with a lot of waste or you'd end up with too much product. It might have been, Hey, we shipped that warehouse a palette of the SKU every week because that's what we've always done, but it turns out they're really only using half a palette a week or maybe they're using two. And so that data visibility lets you do the right amount of product in a much easier way can also be used for many other things. If you think about, just from an industrial engineering perspective, managing and monitoring your performance, right? Being able to go through every functional area of the warehouse and identify this area is performing well here. These operators are performing well to the point where they should be paid an incentive. And then you have a lot more data to enable that type of thing to take place.

Tom Raftery: 12:33

Okay. And can you do things like heat mapping of warehouses and work out safety incidents and work to improve them? Anything like that?

Andy Williams: 12:42

Absolutely. Yeah. You know, all of these operator stations there's tracking. So whenever there's an operator present, that's interfacing to the robots you know, specifically which operator it is, when they were there, what activities they were doing, exactly everything that was going on, so I think there's, there's a lot more that can be done from a safety standpoint as well. And in addition speaking of safety, it's just generally much safer. You know, it almost goes without saying, but if you have to, go and physically remove a 50 pound box from a shelf in order to be able to pick something, you're going to be much more prone to injury or something falling on you. If that's coming to you, and especially if it's in your golden zone, it's going to be more ergonomically friendly and you'll have a higher sustainable performance and ultimately a happier workforce as well. And honestly, that should not be understated. Yeah, workers in these systems typically really enjoy it a lot more so than walking 10 miles per day. You know, you don't have to expend the same level of energy. It has this sense kind of being a game. A lot of times they're trying to do better than their counterpart and having fun with it.

Tom Raftery: 13:54

Yeah, because that was going to be my next question is, you know, the workforces, how do they take to these robots? Initially, there must be some kind of trepidation, at least.

Andy Williams: 14:06

Yeah, I think, you know, sometimes that is a real issue. So, you know, workforces can hear, Oh, we heard that there's going to be an automation project. And does that mean job loss? Typically what it really means is that, that's that same number of workers can produce a lot more than they could before with, with the help of robots. And it can mean, some different types of jobs as well that are higher paid jobs. You know, maybe there's technicians supporting the robots or software people supporting the robots. So there's definitely a change management element that goes into it. But generally speaking, the warehouses that are automated have happier workforces in my experience, partly because they are much more productive. And they just don't have the job itself isn't as hard.

Tom Raftery: 15:01

Right, yeah, that makes sense. That makes sense. We've gone through a weird period, I wanna think the last couple of years, and you know, we're kind of in uncertain times economically at the moment as well. What kind of challenges is that leading to for logistics leaders, for example, you know, how are robots able to help

Andy Williams: 15:25

Yeah, some, some big challenges. There's no doubt. You know, COVID produced some strong macro level change. It really increased the level of e commerce, which was already you know, quite booming. It, it brought alive some new segments you know, so e-comm grocery, but, but also the cold chain you know, so frozen pizzas, all of a sudden there were warehouses full of nothing but frozen pizzas, you know, during covid. So, not quite as intuitive, but definitely some big change. And then, of course, as covid slowed down some networks were overbuilt. Amazon, I think that's public knowledge kind of overbuilt. Right. And then had to really slow down that had some big impacts on everything. You know, and now we're in a new phase. We have I think still some major workforce challenges and we have inflation. The cost of money has gone up significantly as well. So, it It is a challenge for leaders. You know, I think we've seen a lot more projects that are focused on long term supply chain transformation. So, not as much you know, one off facility ROI based. But, hey, how can I, utilizing these new technologies, really change my supply chain in a substantial way? Whether that's reducing the number of facilities, literally just changing the amount of product we have at each node in our supply chain by leveraging these new technologies to reduce inventory cost and increase service levels to customers. But you know, there is also so those are making for a different business case, obviously, when you're when you're looking to propose those as a logistics leader. But and you also have you know, a very real challenge right now, which is just the, you know, the interest rates have gone up a lot, right? And I think especially for small to medium sized companies, this is having an impact on their ability to, you know, spend large amounts of capital. So, you know, very much looking at, you know, what that means from a robots as a service perspective, or is there an easier way to, you know, enhance productivity in many cases as well?

Tom Raftery: 18:53

Okay. Okay, cool. And for organizations who are thinking of maybe researching or embarking on a robots project, what would be first steps?

Andy Williams: 19:09

Yeah, I think the first step is trying to put effort into understanding your own business. It's, it's surprising. Sometimes we we interface with people, they, they don't really have any sense of what, what they're doing logistically, you know, they don't have the data even at a, at a very top level. Right, right. So I, I think, you know, being the master of your own destiny to extent, making sure, you know, at least at a high level what your current situation is and, and what the challenges are and, and how does that interface with your strategy, you know, and at that point in time if you've identified some areas to explore, there are, two basic ways that you can, understand things. If you have engineering talent, if you have inquisitive people in the company problem solving mentality, if that's part of your DNA, certainly a great way is to just go directly to the market. You know, there are lots of available providers doing investigation that way. If, if your organization is too complicated, too many stakeholders uh, too nuanced from a software standpoint or if you just don't have the, the resources or capabilities to do a big, you know, engineering project, there are many different consultants in the market that would be more than happy to assist you with that. And are quite capable. And they are typically very plugged into all the different providers and generally can make recommendations about how to move from Step a) discovery all the way to the end result. And you know, progress you through that process in a logical manner.

Tom Raftery: 20:51

Okay. Do you have any kind of case studies, Andy you can talk to? Kind of customer wins where you know some customer has had no robots, and now they have loads of robots, and their productivity has gone from zero to 10 million. Something like that.

Andy Williams: 21:08

Yeah, well, an easy one that that comes to mind. We had a really super successful project with a company called Ariat, and that was with our partner Hitech acting as an integrator. And, and they, you know, Ariat say is in a growing apparel brand Western wear, cowboy boots you know, outdoor clothing, that sort of thing. And they experienced a lot of growth in, in e commerce, which was, they hadn't really experienced that before and in other parts of their business, they'd always been manual. And, you know, so they started thinking, oh, wait, we're, we're having a bit of an issue here. You know, we're growing and we can't handle our projections anymore, we need to do something. They contacted HiTech who acted as a consultant and yeah, so they went through a design and decided to buy a new facility and they went from their average operator picking you know, about. 75 pieces an hour to clo closer to 300 pieces an hour. Wow. So, you know, and, and, and achieved an ROI less than three years. So I think that's a relatively typical example. And one that's very attainable not just in the apparel industry but a bevy of other industries as well. You know, retail, wholesale C P G you know, beer, spirits, and, and many others as well.

Tom Raftery: 22:34

Okay, nice, nice. And we've seen this incredible evolution of robots from very, very primitive ones 10 years ago, maybe more to the sophisticated ones that we have now. What are we going to see in the next 10 years for robots and the software that operates them?

Andy Williams: 22:55

It's a great question. You know, the evolution has been amazing to see. Just 10 years ago, really robots were a bit of an afterthought in the warehouse. And you know, I think Kiva you know, together with maybe AGVs and automotive, you know, started to kind of open everyone's eyes. Certainly when Amazon purchased Kiva that was responsible for. You know, or rather it was a catalyst for a lot of robotics companies to enter into the market. And since that point in time you've seen some really rapid evolution, and it's, it's really become, how much performance can you get out of the smallest space possible with the fewest number of touches possible. And still, you know, providing all of this flexibility that we talked about earlier with sequencing and everything else. So there are only so many things that are possible electromechanically. And we're getting closer to, I say, the limit of you know, being able to do the highest performance possible in the smallest space possible from, from an electromechanical standpoint. But the difference really is the software. So, you know, the algorithms that run one robotic system need to interface with the algorithms that run the next robotic system. And, you know, certainly we see AI and machine learning. You know, having a big impact in the future here, and I think that's where the majority of step change will take place. So, one common application is in piece picking robots. So, you know, these robots use vision systems and they implement machine learning to, you know, continually improve, find the next best way to grasp an object, share that information with the rest of the systems to continually learn and improve performance. And another way is I think simply the management of flow, you know, it starts to get very, very complicated, you know, when you start thinking about, hey, yeah, I have this really dense system. And it's very high throughput performance and it's got all these different priorities like we talked about earlier. It has to be here at a cut, a certain cutoff time. Oh, and the same system needs to serve my B2C channel or direct to consumer channel. But I also need to build pallets from the same system to serve my you know, my retail customers. Right. And, and I may have some other, you know, different specialized flows in there as well. So it very quickly goes from, evaluating a few different parameters in your algorithms to all of a sudden thousands. Yeah, so I, I think, you know, AI in the warehouse. Yes. But of course the unlock and we talk about the orchestration engine that, you know, robotics systems can be for the supply chain. But, but you know, the, the thought about, you know, different types of AI connecting the warehouse to the other parts of the supply chain. So really optimizing, from manufacturing all the way to the end user. Doing it in the most efficient way possible, right. And, and minimizing all of that waste that typically has been residing at different nodes of the supply chain. Well, while, at the same time improving service levels and making same day delivery just as an example possible.

Tom Raftery: 26:40

Okay. And what about, I mean, we've all heard a lot in the last few months about the likes of ChatGPT and large language models. Would something like that interfaced with a voice module, for example, enable a user interface, which meant people in the warehouse could talk to the robots and the robots reply using a ChatGPT like interface, but just using voice as well. Would that be of, would that be something that would be useful? I mean, it never worked in a warehouse, so no idea.

Andy Williams: 27:11

Absolutely. Yeah, there's no doubt about it. You know, we may have 10 different languages being spoken in a warehouse. And you can see a lot of applications there, you know, voice picking as for a very long time, been a staple in certain industries. You can see applications there. A company recently came out with an AI, a large language model, I guess, prototype system that was designed to kind of perform that consulting function we talked about earlier. You can see lots of applications where you know, there's a touch point between a human operator and the machine for sure. We'll see those and then we're also going to have a lot of these more technical applications, which I think are based around, you know, optimization of material flow, grasping certain items with machine vision, automatically synchronizing the inbound and outbound flows to the supply chain. So just at the beginning there but it's going to be a big area of growth and is going to be responsible for some major impacts in the next 5 to 10 years, probably faster than we think based upon the way things are going.

Tom Raftery: 28:24

Great. We're coming towards the end of the podcast now, Andy. Is there any question I haven't asked that you wish I had or any aspect of this we haven't talked about that you think it's important for people to be aware of?

Andy Williams: 28:37

I, I think the most important message to me for really everyone to, to understand is flexibility, I think is critical, right? And what I mean when I say flexibility is that in the past, it was so difficult to design a highly automated system. Of course, those were usually fixed pieces of automation, highly mechanized and they relied on some really dangerous, risky projections about business strategies into the future growth percentages, percentages, And, you know, lots of effort was, was put into making those as precise as possible. And invariably, of course, they were wrong. And then at that point in time. You could be stuck with automation that wasn't producing the results you expected because your business changed. And today with the advent of robotics, you don't need to approach the situation with the same level of precision. If you know, kind of, a direction you're going in, that can be good enough to already realize value quickly. So a fast time to value while being insulated from these constraints of the past. So just as an example, if I'm a business and I don't know my future from a channels perspective, I don't know what my mix of B2C or B2B really will be, well, today's modern robotic systems, that's okay. You know, if it changes from being 90% carton to 90% tote, today's systems can accommodate those types of variations. If I'm guessing that I need 10 inventory days on hand now with 100,000 SKUs today and it turns out that, oh, I really need to do, 150,000 SKUs and I'm willing to accept a fewer, a couple of fewer days on hand, but that still means I need a little bit more storage space. These systems can very easily in the matter of days or weeks be expanded from that point. If my order profile dramatically changes, so, you know, to where I've got, lots of e commerce volume coming in, which drives up the throughput of the system on the order side, robots can be added in easily into that same system to support that growth trajectory as well. So having that flexibility mindset from the beginning is important, right? And, and saying, Hey, whatever I'm considering, how sensitive will this be to the unknown fluctuations in my business or macro environment issues that I know are coming? How will it adapt and what will that mean? So, you know, scalability? Yes, but really flexibility. And, you know, and while at the same time being able to take advantage of a lot of those advanced capabilities we discussed earlier.

Tom Raftery: 32:00

Fascinating. Andy, if people would like to know more about yourself or about any of the topics we discussed in the podcast today, where would you have me direct them?

Andy Williams: 32:12

Yeah, you can find us very easily on the web at ExoTec. com and LinkedIn or anything else. But if you'd like to contact us, just go to ExoTec. com. There's a button to mash and we'll be there to answer the call.

Tom Raftery: 32:27

Superb. Superb. Andy, that's been great. Thanks a million for coming on the podcast today.

Andy Williams: 32:32

Tom, thank you very much. I enjoyed it.

Tom Raftery: 32:34

Okay, thank you all for tuning in to this episode of the Digital Supply Chain Podcast with me, Tom Raftery. Each week, over 3, 000 supply chain professionals listen to this show. If you or your organization want to connect with this dedicated audience, consider becoming a sponsor. You can opt for exclusive episode branding where you choose our guests or a personalized 30 second mid roll ad. It's a unique opportunity to reach industry experts and influencers. For more details, hit me up on Twitter or LinkedIn or drop me an email to tomraftery at outlook. com Together, let's shape the future of the digital supply chain. Thanks. Catch you all next time.