When supply chains face external disruptions, voice-directed solutions can get them back on track
For the latest episode of our manufacturing podcast, Data In Depth, we sat down with Alex Reneman from Mountain Leverage. Alex explores how manufacturers can leverage voice-directed solutions to reduce downtime in the supply chain. He discussed how these solutions are particularly effective when employees may need on-the-spot training to help adjust for social distancing measures.
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Announcer: Hi and welcome to Data in Depth. a podcast where we delve into advanced analytics, business intelligence, and machine learning, and how they're revolutionizing the manufacturing sector. Each episode we share new ideas and best practices to help you put your business data to work. From the shop floor to the back office, from optimizing supply chains to customer experience, the factory of the future runs on data.
Andrew Rieser: Welcome and thanks for joining us for season two of Data in Depth, the podcast exploring data and its role in the manufacturing industry. I'm your host Andrew Riser. Today we are joined by Alex Reneman, founder of Mountain Leverage. Welcome Alex.
Alex Reneman: Hey, thanks Andrew. Glad to be here.
Andrew: Yeah, looking forward to chatting. Really enjoyed our pre-conversations leading up to this and doing a little bit more research about yourself and Mountain Leverage. But before we dive in, it would be great if you just tell your own personal story of what led you to find this passion and ultimately create and found Mountain Leverage.
Alex: Yeah, it's interesting. So it was, I guess, back in '04 is what we're talking about. I had already spent some time in post-ERP implementation, so big accounting systems at the time, handling data integration and data transfer. And I spent about 18 months give or take on on deployment to Iraq. And on the way back in '04, I was just kind of looking for different options and looking for, I've always kind of had an entrepreneurial spirit, or a streak in me and a buddy of mine called me up and said, "Hey, there's this opportunity in Pittsburgh. "This voice company needs some help "with their customer backlog." And I thought, well, okay great, I'll do that while I'm figuring out whatever else I want to do. And so in that process, that was the introduction to voice technology as a technology for directing or documenting work. And at the same time I was really building what was Mountain Leverage, and that was to be more of a kind of an onshoring web application company here in West Virginia. And we always would joke, so the times zone was pretty good, language barriers, okay, as opposed to whether it was India or China at the time for US. And so I had, as the business grew, the work continued to grow in the voice space. And so we got to a point where about half of our business was in voice work and half of it was in web application development. And they're both fine pursuits, but we found that one is a commoditized market where we were just one of many. And the other, the voice side, we were really good at it and it was great work and we really enjoyed it. And so really at the end of '07, we all looked at each other and said, look, it's time. We're going to transition everything to voice. And the majority of our business became voice. So we trained up those that weren't on the voice side and really kind of went down path, starting primarily just in services of developing systems and customizing systems for customers and other partners, and kind of growing from there to training and implementing. And then actually selling on our own and being out our own customers, and building our own products. So it's been a wild ride really.
Andrew: Yeah, that's a fascinating story and it's always fun to talk with other entrepreneurs. I myself originate from West Virginia, have a similar type story, and live down in Charlotte now, and founded Mountain Point. And so always good to cross paths, so appreciate you sharing that background. As we pivot into today's discussion, obviously the elephant in the room is COVID-19, with everything going on with this global pandemic. And I'm curious what your perspective is, as you see not only impacts to businesses but this new normal that everybody's driving towards. So I think that the world has already started shifting and digital transformations were taking over, and technologies like voice were probably there. But I'm curious to see how this is shaping up what you feel will be the new normal, if you will.
Alex: Yeah, I guess I could just say everything's changed, and then we can move on, right? And nobody knows what it's going to be. And really I don't have any special knowledge there either. I wish I did. I think there are a lot of people that wish their crystal ball that people talk about, they really had one. That said, I mean, I think there are things, we've seen things change. Ultimately things have changed. But I think things are gonna continue to evolve and change. And in the areas we play, which really, I mean you mentioned voice was around, and it has been. Really, the primary industry that really took off and leveraged voice-directed work as a solution was really in distribution and supply chain. So these are folks running around the warehouse picking products, putting down goods, that kind of stuff. And so there's an efficiency and an accuracy there, and we can talk more about that later. But we, Mountain Leverage, has to have taken an opportunity to take that same kind of technology and apply it across various industries. There's interest, but maybe there wasn't really demand. And certainly, now we're seeing, with things happening, with COVID-19 we suspect it's gonna be continued some more demand in some of those other areas. And even in the supply chain as well. I mean, staying right in supply chain obviously buying habits have changed. I mean we look at now things have definitely changed, and they're going to continue to change, and even access to employees, and the subsequent needs that will come from this pandemic on employees and labor. The manufacturing slowdowns, the supply chain in terms of limiting goods, movements, and those kinds of things. Those are all things that I think we're going to see, as a challenge and opportunities, really kind of going forward.
Andrew: Yeah, for sure. Are there any specific scenarios that you'd like to dive in a little bit deeper with respect to that? So you hit on supply chains, maybe you can like pick one or two industries and then maybe we can just have a conversation around what you're seeing those impacts or transformations evolving to.
Alex: Sure, I mean, I think if you look at where it all starts, on the demand side, so buying habits as we know have changed. I mean going to a grocery store, I think, is gonna be very different going forward. I mean people are now doing click and collect, or whatever the certain brand would call it. The idea of you ordered online, drive by, and get it loaded in your car. That was kind of a novelty and there was some adoption of that. People are gonna be much more comfortable with that going forward now after having to do that, and in some cases, in some areas. And so that's really one example. And on the surface that seems pretty simple, but really the logistics behind that in terms of having now your store personnel becoming distribution personnel, and going and picking the products and making sure they have the right amount, the right type, making sure it's done in a timely manner. The visibility to the shopper now to know when their order is going to be ready. There's all kinds of ways to innovate in and around there. And what it may do in many cases, for like a grocery stores, for instance, many of those may become more dark stores where there's not folks in there shopping. It's really more of just a mini-warehouse if you will. And so there's a lot of ways that could go. And of course some of these pressures, as you mentioned earlier, they were there before. The eCommerce demands would be putting on distribution and manufacturers for awhile. The idea of previously, a warehouse might be able to ship a case of goods to the store, and with the eCommerce pushing when people ordering online, well now that that warehouse has to deal with shipping eaches. So instead of sipping a giant case, which is complex in and of itself, now it has to ship eaches and the additional visibility that people are going to want to expect in that. That's all changing. And I think it's going to be really be be ramped up in that, in that retail space, which I think is going to be a real challenge for a lot of folks that haven't optimized, or you know the phrase you keep hearing is implemented the digital supply chain to be able to handle that kind of complexity and that kind of demand that going to happen going forward.
Andrew: Yeah, I couldn't agree more. I think that every day I'm seeing local businesses changing up different models. I'm seeing even more progressive, like mobile apps that have been around now adopting and empowering some of these local businesses as well. So a simple example that comes to mind is the app DoorDash as an example where you can, and now has pickup as an option. So all these stores were able to quickly jump on the business model that already existed there with DoorDash, by having these gig economy workers be able to pick up your food and deliver it. But now it's also empowering you to do the click and collect method as well.
Alex: That's right. And some of that's even diminished brand strength. I mean because of, for instance, I mean everybody makes it, right? You're brand toilet paper is out, but you're gonna be told that, you're going to get something else. And in that really extends to other brands. And so I think substitution at this point being more acceptable, really kind of changes how a lot of retailers operate too. And it may erode some of the power that some brands had in the past. It'll be interesting to see that play out.
Andrew: Yeah, for sure. So let's pivot a little bit to dive into voice some more. So maybe you can just kind of give some scenarios around the warehouse worker and the picking process, and maybe talk the basics of how voice comes into play and the benefits of it and then where you see that kind of evolving to.
Alex: Sure, so I think if you look basically at a warehouse, it could be many football fields wide and long, it could be fairly small, but really it's a box full of boxes, full of stuff that it's picking, packing and shipping. And that seems really simple on the surface. And if that was it, then it wouldn't be such a complex arena. But there are a lot of things going on to make that pick, pack and ship work. And where we come in traditionally and where we've been able to see a lot of value is at the execution on the floor. So an order comes in and you have currently in a traditional model, you have an individual that'll go in and pick that product, whether it be several products to go to an individual or a store or what it is. We actually drive that person through the store with voice telling them, go to this aisle and pick this product and this quantity, and there's checks in place for accuracy. And what you have traditionally is, whether it's maybe it's paper, maybe it's scan guns, and you run into some issues, whether it's accuracy from a paper perspective, accuracy is an issue. Or you end up slowing things down to make sure you're more accurate with a scan gun. And so voice, in many scenarios, can really make a more efficient pick, as well as a more accurate pick. And so that's what's happening. And then there's a wireless communication from the device that on the user, or on the forklift or whatever it may be, that communicates back to the warehouse system that says, "okay, we've got the goods "and now we'll send it to the next one." And so there's a kind of a constant communication, which gives visibility to display chain that maybe wasn't there previous with a paper solution or something like that. And so I think that's really the traditional use. And what we found over time is, I mean, we were voice guys just coming in and implementing voice, but we've found really the ability, what's really needed, it's workflow optimization. No matter what the technology is, is it voice, is it something else, and it's about visibility, and those two things are really key, to I think, from a standard distribution standpoint.
Andrew: Yeah, absolutely. So the way I always describe it as people, process, technology and data. And I think what you're finding, as you just described, is technology is typically the easy part. It's that workflow optimization and the business process optimization. It;s the training and empowering of the worker in those scenarios. And then most importantly the trends that we're starting to see is how do you really take advantage and leverage that data. So maybe you can can shed a little bit more light on as all this is evolving and as you're unpacking these scenarios and diving deeper into the integration of these systems and the workflow optimization, how do you guys approach data, and where does that fit in with the bigger picture?
Alex: Yeah, that's a good question, and that's a question we're always asking ourselves is, okay, where is the data? What value is the data, and what can we do with it? And what can we make it say, or how can we use it in value? You mentioned labor, and we use that as an example. Traditionally labor, even most recently, the challenge was, where do I find the workers? We were running out of space, how are we going to solve the labor problem? But what we found is, so if we look at what data exists, I mean there's a lot of tribal knowledge that sits in some workers, you can put into a system. And so we take some of that data and put it into a voice system that can. Let's use an assembly plant for instance, and we can voice-enable, the process so that maybe you have a flex worker who is at one station and they're fully trained on one station, and maybe they're only partially trained on another station. And they really wouldn't be able to work through that. But you add you know, a display with voice that walks them through the process. Maybe they're less efficient than if they were fully trained on that station, but they're able to get it through. And so that is that that's something that's pretty impressive normally. But then you put the COVID-19 lens over it and now that individual can be effective, while maybe their partner is out with COVID-19 or unavailable based on distancing and different things. So that's where we find some of these solutions really interesting at these times. And it puts a situation where not only that, you have workers, now there's more even more competition for workers to a certain degree. And you find that you can leverage the data in a way that, that kind of hearkens back to the days of old. And we jokingly say, way, way back in the day, the manager might've known that the Bob on Tuesday isn't going to perform as well as he does every other day, because Monday night's his bowling night. And now he's going to stay out late and drink too many beers, and he's going to come in and be a little slow. And so the manager knows to put Bob on some other job or whatever it is. Well, that intimacy is a little tough in today's world, especially with the turnover of work and things. But with data we can go in, and we can begin to find trends and know that, hey, Bob on Tuesday isn't his best self. And so it doesn't take the level of intimacy that it used to, we can use data to do that. And there's lots of arguments of for or against that. But there's just some really neat things that you can take that data and actually apply it in a way that makes everybody more efficient. And if for instance, you can take that Bob and say on Wednesday, you can coach Bob, you can give him updates of where he's at, and kind of coach him in his work. So he feels like he's getting something accomplished as opposed to just go here, do this, or just see a screen that pops up a bunch of numbers and it begins to make worker satisfaction better. So retention is a big thing that folks kinda struggle with. And those are some of the areas we're seeing our customers really have a lot of interest.
Andrew: Yeah, I think that's a great analogy and a good example of where this data can be leveraged. So you had also mentioned to me about the black box of just in time manufacturing and supply chain. can you expand on that a little bit more? Maybe share some examples around what you mean by that.
Alex: Yeah, I think this one will be hotly debated for a while. I mean, I get the whole idea of just in time delivery, right? It's this lean supply chain, and we don't have a lot of things laying around. And the whole focus traditionally was to compress this thing from the time it's manufactured to the time it's in the customer's hands. That said, we see some that break down moments like this, in moments like pandemics. Not that they come every year, thankfully, and hopefully they don't continue to come this often. That said, it did reveal, I think, some weaknesses, and some things people will be looking to address. And I use the example, of it's good to be lean, but at the same time, a little extra fat can get you through a famine. And in these situations we saw where lean kind of broke down a bit. So I think of course you're still always gonna be looking to cut waste out of processes. But I think just like in our immune system, we're carrying around antibodies for diseases we haven't seen ever in our lifetime, but we carry them. And if we ever did bump into them, we've got them. And so that's a little bit of extra effort, but it's, it's something there. And so I do think we'll see an additional cost of folks being willing to carry an additional cost to insulate a little bit with this, whether it's from a safety consideration or a supply consideration. When you look at what's happening today, you'll see that some people are single-threaded in terms of their location. Maybe they're trying to put all of their product out of one DC or out of one plant to manufacture it. And there's a lot more discussion now about, maybe we need some fail-safes. We need multiple points for this, which previously, the last few decades, they've been trying to remove those multiple points to have it more streamlined, and it kind of broke during this. So I think that we're seeing a lot of folks interested, but you still have proponents. So I think that as an all things, there's a balance somewhere in between that this experience will at least maybe bring some of that back. That okay, maybe it's okay that we have some fail-safes here. And really when you talk about the focus on manufacturing, and depending on what your business model is, obviously, but in most cases, the C suite really isn't interested or focused or maybe doesn't have any idea what goes on inside their distribution center. But right now, that's front and center. And so I think going forward that's going to be a C level discussion. It's going to be a C level interest and folks will be wanting to know what's happening in distribution, where are things, how much technology we applied to distribution so we can turn on a dime in the event of something like this, unfortunately like this pandemic, or anything. Weather related events, all those things have over time exposed how important supply chain is to a manufacturer and retailer.
Andrew: Yeah, for sure. So one of the kind of additional thoughts that I have tying this all together is for the future of voices going. So I'm sure you're already starting to see, and things like artificial intelligence being interweaved into this. We've seen the kind of uptick of things like Siri and Alexa, and a lot of it's been transactional up until this point, but I'd love your insights on where you think AI is going to play into this and how kind of this natural language is going to open up those doors a little bit more for more predictive and prescriptive analytics, whether it be the worker or the C suite engaging with their systems and data to shed light on what the underlying systems and AI, for lack of a better description, is uncovering about their business.
Alex: Yeah, I mean that's really the exciting part, isn't it? I mean, they have, the fact, for natural language processing and then what we can do with that, and be able to on the fly pick up applications and let them build themselves. I mean there's some really cool stuff and it will happen. That said, there's still, like blockchain for instance, is one of these things that's talked about in terms of what's coming and it has value, and I believe once there's some standardizations in place, that will help with some of these transactions. But to your point above the transactions, or I guess beyond that, is this idea of where AI, machine learning takes place and from a voice perspective, again, voice is really largely the input. And right now we're, we're primarily, when folks think of voice and voice director work, it's purely directing the worker. When you look at just what we talked about earlier, like the coaching side of things, where we can use data to be able to more efficiently or effectively coach the worker and help the worker. There's also the relationship with other applications, whether it be robotics, or other things within the warehouse where voice is just one piece of the puzzle. That's a great interface to the user. And it can be an interface that gets more lively and more engaging. And so you have retention, you have performance, and you have integration with other modalities out there, whether it be robotics or even some of the traditional, technologies that are out there. But you begin to combine all that together, and that's really what gets you to this whole concept of the digital supply chain, right? And it gets really interesting in terms of the automation that can take place now. There are places today in our warehouse today that have have goods to person. There's conversations about how that works. But again, most of those implementations are all kind of in point. There's this and this moment of this, and this moment of that in the warehouse. But integrating all that together and having some smarts connecting when and where and how, it's pretty exciting. And I think this event, and I always try to find the good in any kind of event, whether it's a pandemic or something small. And in this case, I do think there's going to be a ton of innovation and people being interested for how to pandemic-proof their business. And in that, we're going to see a real uptick in a lot of these technologies that we just mentioned.
Andrew: Absolutely, yeah. These are definitely some challenging yet exciting times. So agree 100% that this will spur the next wave of innovation as these companies take the lessons learned and identify where the gaps in their organization and their business models lie, and figure out how to come out the other side of this. Which is also a great opportunity for systems integrators to help play a part in these digital transformations and optimizing these new business models and, and being the glue that kind of connects all these systems and data together, which is also pretty exciting.
Alex: For sure.
Andrew: Cool. Well, Alex, I really appreciate your time today and joining the show. A lot of great insights and great conversation. Any parting words or last thoughts that you want to leave the guests with?
Alex: I guess I just would like to mention what we're doing in healthcare. So we're a geographically distributed company and we have folks all over. And so we've each reached out to our local areas and beyond for how we might be able to help them from a patient intake perspective on COVID-19. And in those cases it's kind of overwhelming and maybe the systems aren't there to capture the information needed for contact tracing or even just storing and contacting those folks after tests have come in. And so as the testing ramps up here in the United States and around the world, we hope to be able to provide something and to help. And so it's just one more area where innovation you're using a technology that's traditionally used elsewhere to really help in an area of need. And so we're kind of excited about that. Hopefully, we can make a difference there. I know lots of companies are looking for how they could, well we don't have a plant that we can retrofit for masks or vaccines or anything like that, but we can certainly maybe help the workflow for healthcare workers, which would be fantastic during this time.
Andrew: Yeah, absolutely. That's always great to hear a businesses figuring out how they can give back, especially in times like this. So thank you very much for sharing that.
Alex: Hey, thanks.
Andrew: For those that are listening, if you'd like to learn more about Mountain Leverage and their solutions, I'd encourage you to visit their website at mountainleverage.com. And if you'd like to connect with Alex, we'll be sure to provide relevant links to online profiles in the show notes. If you enjoyed this episode, please take a moment to rate the episode and subscribe to Data In Depth, available on iTunes, Google, Spotify, Stitcher, and pretty much anywhere else you might consume your podcasts. Thanks again for joining us today.
Announcer: Data in Depth is produced by Mountain Point, a digital transformation consulting firm focusing on the manufacturing sector. You can find show notes, additional episodes, and more by visiting dataindepth.com. Thanks for listening and be sure to subscribe wherever you get your podcasts.