Transcript 0:00 [on hold music] Welcome back to The Peggy Smedley Show, the podcasting voice of IoT and digital transformation. [on hold music] Hello, listeners, and welcome back to The Peggy Smedley Show. 0:14 Boy, we've had a great show for you today. My next guest today is an execution-focused entrepreneur with hands-on experience in starting, scaling, and managing ventures focused on twu-- tough emerging markets. 0:28 Please welcome Arka Dar, CEO and co-founder of Zener. Arka, welcome to the show. Thank you very much, Peggy. It's a pleasure to be in the show. Hey, it's a big day for you today. You and I talked briefly yesterday. 0:43 Come on, you have to tell our listeners, you know, a twenty-two million dollar funding day is a big day for someone. It's a very exciting day at the company. We just announced the closing of our Series B round. 0:55 We are fortunate to be backed by some incredible investors like Excel, Founders Fund, Qualcomm, Nokia. 1:02 It's, it's going to be a fantastic year, and I'm, I'm so happy that, uh, we're getting to share the news with you on your radio show today. 1:09 Well, we're delighted to have you on because you guys are doing some really great things when you talk about things that are happening in the Internet of Things, but more importantly, when you talk about what's happening in field service, I think it's a really important area to actually be talking about and just fundamentally how w-- the work in the field is changing today, and that's really why you ended up getting this next round of funding because you're actually changing the way things are done. 1:37 Let's talk about that for our listeners. No, absolutely. I, you know, you're absolutely right. 1:43 So we are kind of at the inflection point where, you know, these, these field service teams, they're being asked to do incredible amount of work with, with even less resources, and they're going to be strained to the limits, right? 1:55 So as the 5G starts getting rolled out, uh, we will see these large telecoms and these network providers who have to go out there and, and, uh, build out incredible amount of infrastructure in very little time. 2:09 And field service, the way we know it, is just not going to be able to keep up. So we are, we are definitely seeing a fundamental shift. 2:16 We are seeing a lot of focus on driving efficiency, driving automation in that world to, to really enable that kind of large infrastructure play. Um, the technical complexity in the field has gone up. 2:28 We are asking our technicians to go out there and install and fix and maintain a, a constantly increasing and changing environment. 2:36 So, you know, it, it's going to have to go through a very drastic change to kind of keep up with the pace. And, and that's where we are really positioned as a company. 2:45 You and I were talking yesterday briefly when we were really trying to understand how the markets are changing, a little bit about how IoT is changing, but more importantly, how artificial intelligence and machine learning is coming to play-- into play. 3:00 And you guys are really looking at how artificial intelligence is really changing this marketplace. 3:07 And you guys are really positioned very well when you look at about how your platform is really kind of changing the way people are going to look at things. 3:17 'Cause I think people get confused now when they hear about IoT and AI and machine learning. 3:24 I think there's a lot of different ways, and I think what you're gonna be able to do is really define how service is being performed. 3:32 And I think specifically, just like you were describing how telecoms and energy specifically there, and eventually how you'll be able to do this in a lot more verticals as time goes on. Isn't that correct? 3:45 That is, that is absolutely correct. I mean, you know, like AI, IoT, for some very unfortunate reasons, they have been reduced to buzzwords, and, and we hear them all the time now. 3:55 But, uh, they're incredibly powerful technologies, and they're going to change how we operate in this world. Um, data by itself isn't all that powerful, isn't all that useful. 4:05 You need to be able to apply AI to, to glean insights, uh, from the data that, that really help you drive actions. 4:12 And, and I believe, you know, when it comes to field service or these kind of infrastructure-heavy spaces like telecom or energy, um, to, to really become a predictive, um, um, an automated predictive, uh, process, those kind of data insights, AI is going to play a very, very important role. 4:32 Um, when we think of workflows on the ground, we, we, we try to separate it in two distinctive processes. We have the back office, we have the front, front office or the field engineers. 4:41 And when you look at how work gets done today, you know, scheduling technicians, managing work order, um, assigning those work orders to the right person, figuring out what parts and inventory needs to be in the trunk, uh, of a truck, uh, so that the work can get done properly, those things are manual processes. 4:59 There's a lot of manual decision-making, and they take away a lot of time. 5:04 We, we see operations where one back office coordinator is going to be managing just a handful, three or four field engineers, and those processes don't scale. Uh, they are prone to error. 5:15 And when you put that kind of a field organization under massive pressure to really go and deliver on the field and quadruple their amount of work that they have to get, you know, the, the amount of work they have to complete, it really forces them to rethink processes. 5:30 And, uh, and I believe AI, IoT is going to kind of drive us in that direction. It's going to help us automate those processes, but it's also going to really help us become a lot more predictive of a-- of an organization. 5:43 Um, we will see work origination happening straight from devices. We are, we are going to have this big kind of space of devices which are connected to the network. They're going to be talking to other systems. 5:56 They're going to predict failure. 5:58 Um, you know, a telecom tower that operates in the winter in Chicago, it undergoes very different, uh--tier and, and depreciation than a tower in, in Los Angeles, and that's just millions of data points. 6:13 So how do you kind of automatically figure out, okay, I have a tower which is about to go down. These are the five probable causes of why it's going to go down. 6:21 I need to find the guy with the right skills, with the right parts in the truck who can show up and do that work. But, you know, we talked a little bit about different workforces as well. 6:30 So there is a lot of different parts- Well, yeah, you talked about- -moving parts here. Yeah. You talked yesterday, which was... 6:36 I really love the expression that liquid workforce versus that on-demand, and that's where those expertise comes in because not everybody's going to have the right expertise, and that's where that knowing that AI platform that you have is going to put the right technician in the right place at the right time, and that's really very important. 6:57 Talk a little bit more about that. Yes. So, you know, the, the concept of blended workforce is kind of already in existence. 7:04 A lot of companies, you'll see batched employees, and you'll also see this on-demand kind of contractor base that they kind of rely on. 7:12 But as you blow up the amount of work that needs to get done, we will see a lot more dependency on this liquid workforce. But, you know, the liquid workforce, they operate very differently. They have higher attrition. 7:23 They don't necessarily go through the entire formal training process that a company has in place. So technology needs to do a lot of heavy lifting. They have to do a lot of hand-holding of these technicians. 7:35 Um, they have to become a lot more prescriptive, and, and it really has to kind of get to the point where the application is contextually providing you with feedback and information to help you best get the work done, completed with an incredible first-time fix rate. 7:53 Um, what I really mean by that, Peggy, is, you know, you're a new technician, you join the platform. The, the application needs to be able to learn your strengths and weaknesses. It needs to become very, very contextual. 8:05 It needs to get to a point where it can understand that, you know, nine out of ten times, you have done this task properly, but that one time you failed because you had a couple of missteps in these two part of the process. 8:17 So the technology has to kind of learn that and really make a contextual knowledge base available to you for you to be able to get that work done. 8:25 Um, as we see the workforces moving more and more towards this blended workforce, um, where there is a big dependency on liquid workforce, we're going to see those kind of technology playing a very important role in, in, in field service. 8:38 And it's going to cover the entire spectrum. Everything from back office to a field engineer doing a task, to work verification, and then continuously predicting failure. 8:48 Like, across the board, we are going to see those applications. 8:51 Arka, we're out of time, but Arka Dhar, CEO and co-founder of Zinier, can you please tell us where l-listeners can go to learn more about what you guys are doing? It's great. Absolutely. Thank you. 9:02 Um, so we are Zinier, and our URL is www.Z-I-N-I-E-R.com, zinier.com. Thank you, Peggy. All right. Well, well, thank you. We wish you the best of luck. 9:14 All right, listeners, we are out of time, but you know we are broadcast live every Tuesday at twelve PM Central. You can check out our website at connectedworld.com or our past archives at thepeggysmedleyshow.com. 9:26 But of course, tweet at us at ConnectedWMag. We wanna hear what you wanna listen to. 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