The Role of IoT & Big Data in the Supply Chain

Ryan Chacon is joined by the Co-Founder of Nexxiot, Daniel MacGregor, to discuss IoT and big data’s role in the supply chain. Daniel and Ryan open the podcast with a conversation about the current supply chain landscape before moving into the relationship it has with IoT and big data. Daniel then gives advice on selecting the proper IoT components and partnerships. The podcast wraps up with him talking about what these advancements have enabled in the supply chain and the biggest challenges of IoT adoption.

About Daniel MacGregor

Daniel MacGregor is the Co-Founder of an award-winning, multi-million supply chain digitization and IoT company Nexxiot. He is focused on revolutionizing the global supply chain ecosystem by connecting mobile assets and cargo for smooth operations, efficiency, and sustainability. As a pioneer in IoT Hardware, Big Data, and the Connect Intelligent Cloud, he loves building multi-disciplinary, international teams to drive a positive impact on people and the planet.

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About Nexxiot

Nexxiot is headquartered in Zurich and operates throughout Europe and the U.S., employing people from 28 countries. Committed to sustainability through corporate and social responsibility, Nexxiot’s goal is to enable a five percent reduction in global supply chain carbon dioxide emissions by increasing cargo transport efficiency and eliminating waste caused by empty runs and inefficient routes. Nexxiot is a driver of the digital logistics of tomorrow. By leading TradeTech and the digitization of cargo transportation, Nexxiot empowers global shipping companies and suppliers to harness the power of their data through proprietary, cutting-edge technology and integrated data solutions to ensure accountability, security, and efficiency. Nexxiot’s solutions track, find, and protect cargo worldwide.

Key Questions and Topics from this Episode:

(01:38) Introduction to Daniel and Nexxiot

(03:59) Journey of Nexxiot

(06:42) Current supply chain landscape

(09:00) Supply chain, IoT, and Big Data

(12:44) Advice for selecting IoT components

(15:33) Importance of partnering with industry experts

(18:04) What IoT and big data has enabled in the supply chain

(21:32) Biggest challenges of adoption


Transcript:

– [Voice Over] You are listening to the IoT For All Media Network.

– [Ryan] Everyone, and welcome to another episode of the IoT For All Podcast. I’m your host, Ryan Chacon. If you are watching this on YouTube, please feel free to like this video and subscribe to our channel. If you’re listening to this episode on a podcast directory, please subscribe to the channel that you’re listening to it on so that you get the latest episodes as soon as they are out. On today’s episode, we have Daniel MacGregor, the Co-Founder of Nexxiot. They are a trade tech pioneer with a mission to enable easier, safer, and cleaner transportation for all stakeholders in the global supply chain. So we start off this conversation talking about the current supply chain landscape. We talk about how IoT and big data play a role in the supply chain. We talk about hardware/software analytics needed to help create more value and how you can pick the right ones when you’re kind of going down that solution development or solution selection journey. Talk about different business models that IoT is able to kind of enable for organizations and companies who are looking to adopt, as well as talk about different challenges like cultural transformation, how old-school industrial versus new school digital kind of combat each other at times, and kind of overall how it influences and affects adoption. So a lot of value in this episode. I think you’ll really enjoy it. But before we get into it. If any of you out there are looking to enter the fast-growing and profitable IoT market but don’t know where to start, check out our sponsor, Leverege. Leverege’s IoT solutions development platform provides everything you need to create turnkey IoT products that you can white-label and resell under your own brand. To learn more go IoTChangesEverything.com. That’s IoTChangesEverything.com. And without further ado, please enjoy this episode of the IoT For All Podcast. Welcome, Dan, to the IoT For All Podcast. Thanks for being here this week.

– [Daniel] Very nice to see you. Thanks, Ryan, for having me.

– [Ryan] Absolutely. I’m excited about this conversation. Let’s kick it off by having you give a quick introduction about yourself to our audience. Tell us a little bit more about your background, experience, that sort of thing.

– [Daniel] Super. Yeah. So I’m actually from Manchester originally. I moved to Switzerland in 2002. I fancied a change of scenery. I was the head hunter back then, and actually being a head hunter is pretty similar to being a startup founder, because they say, “There’s a desk, there’s a phone. Make some money. And if you don’t, you’re fired.” So you’ve always got this, you know, this runway. And, you know, the pressure’s on. But obviously, also being able to find the early members of the team is an advantage, as well. And it’s just that sort of pace and energy that’s needed to make things happen. And, you know, I had a friend, actually, who I founded the company with. He’s actually left the company now, but he was very technical and we used to sit in the evenings and brainstorm the next big thing that was happening in technology. And, you know, back then, it was sort of around 2008 or something like this, and everyone was talking about machine-to-machine communication. And, you know, I knew that this buzzword “IoT” was on the horizon, and we were diving into what it means. His research was in ultra low-power embedded hardware, and energy harvesting, complex systems, and big data. So, you know, it’s the perfect combination, really, to bring that kind of business and technology together.

– [Ryan] So two questions, one related to the business, one not. You’re from Manchester, so is it United or City do you support?

– [Daniel] It’s Red, unfortunately, at the moment. Yeah. So I’m Manchester United. Since I was a kid, I actually saw Ryan Giggs’ first game if that means anything to anyone.

– [Ryan] It does to me, absolutely. I grew up with English coaches, so they all actually pushed me down the Chelsea path before Abramovich bought them and, you know, they became what they are now. So I’ve been following the EPL since I was really little. So always curious when I meet somebody from over that way, kind of who you support.

– [Daniel] Yeah, I still love football. I still love playing football, actually.

– [Ryan] Fantastic.

– [Daniel] There’s nothing quite like curling the ball in, you know?

– [Ryan] Totally agree with you. So let me ask you about the company a little bit. You kind of gave us a little insights there into the early days. Tell us about kind of the opportunity that you all saw and the kind of journey to where the company is now and what your role is and focus is for IoT in general.

– [Daniel] Yeah, so, you know, I think for me, I always wanted to make as big an impact as possible, and it had to be scalable, it had to be meaningful, and it had to be, you know, everyone was talking about connected coffee machines, and for me, a connected coffee machine is pretty cool, but it’s not gonna change the world. And, you know, I wanted to make a big impact. And in a way, the supply chain is the perfect place for IoT. It’s the holy grail. Since 30 years, everyone’s been thinking about monitoring shipping containers. But it boiled down to this, you know, why is it that you can monitor your pet in the garden, and your child to school, and your luggage through the airport, and your pizza to the front door, right, but you can’t monitor a shipping container full of iPhones across the planet? It really just doesn’t make sense. So, you know, we started to research it, and it seemed, obviously, like an impossible task. It’s been done before. But, you know, we were quite hackers, really, and, you know, bringing things together that didn’t exist and making it at, you know, a price point that’s kind of reasonable, because up until then, you know, we saw a device in the early days and, you know, it was costing probably $800 and it had a flashing light on it. Now, no one’s gonna put that onto a shipping container. So, you know, actually there was kind of, I think, a gap between the technology and the needs in the market, but obviously, as a head hunter or as a recruiter, you’re always asking the questions. So asking open questions, “What, who, why, how, where,” and the hardest of all to answer is “Why?” But obviously, you have to be persistent and get onto the surface of why this hasn’t happened. And actually, when you look at, you know, the reasons for IoT, sort of the slowness in adoption from the original idea, a lot of it is power related. If you’ve got energy, it’s relatively easy, but if it’s a non-powered mobile asset that travels around the world, then you actually have to solve the power problem first. And it’s not a question of how long your battery lasts. It’s a question of how many messages you can send. And, you know, six messages a day, well, if you’re traveling from Germany to Italy and you are only sending every five hours, then you miss the whole of Switzerland. So, you know, this is a no-go.

– [Ryan] Absolutely. Yeah. So tell us a little bit, from your perspective, how do you kind of view the current supply chain landscape, just from a general sense?

– [Daniel] Yeah, well, I mean, words like “landscape” and “ecosystem,” I mean, we can talk about the technology side, but let’s just focus for a second on, you know, what the reality of the supply chain and, you know, it’s come under a lot of focus in the last couple of years and I think people have woken up to its importance. It’s generally considered to be something not very cool. You know, it’s old, heavy industrial objects moving around and, you know, people don’t actually relate it to, you know, eating their breakfast cereal or, you know, receiving their Christmas gifts. But the truth is that we rely on it and depend on it every day, and this made it something that was really, you know, valuable. And I saw the inefficiency in it. And it wasn’t just about the fact that things were disappearing, or things weren’t aligned, or it wasn’t possible to monitor, you know, the location or the conditions of things, but also, it was the fact that, you know, it’s unsustainable. There’s so much waste, gray energy waste, in manufacturing of things that, you know, get lost or damaged, food waste and things like this, but also routing. And, you know, the carbon footprint of the supply chain journey, the transportation journey itself, was, you know, desperately in need of attention. So, you know, it was commercially viable, but it’s also, you know, going to make an impact if you can equip large numbers of mobile assets with hardware and make it more efficient, you know. So we were selling two things. The first thing was, you know, efficiency in your operations, but also digital services to different participants in the supply chain. Because that ecosystem is made up of many different individuals. It’s not just the heavy lifters and the carriers that are moving the stuff. It’s the ports, the terminals, the customs, the financiers, the banks, and insurers, and so on that need part of that data, too. So, you know, you’ve got multiple customers, you’ve got a huge need, and it’s not being addressed. And it was quite outrageous, I felt, so something needed to be done.

– [Ryan] Absolutely. Yeah. And now, what I wanted to do is see if you could just kind of tie that into IoT and big data in the supply chain, kind of the role both of those kind of areas play, the importance of them, and kind of go from there.

– [Daniel] Yeah, so I mean, obviously, IoT devices when they’re deployed and when they’re sending frequently, then, you know, you have a chance to collect big data. And obviously, you know, the device is an enabler. I’ll just show you a few devices maybe. I’ve got a few here. And you know, this is the one that’s going onto the Hapag-Lloyd fleet, shipping container. So it’s the first time in history that, you know, a major shipping line has actually decided to go and deploy these across its dry fleet. And, you know, obviously we get the value out of the data, but the data needs to be contextualized. You know, actually you need to build in and integrate domain knowledge from the industry. And this is an extremely difficult step. So lots of digitalization programs, you know, who owns it? Is it IT? Is it the equipment teams? Is it the commercial teams who are going to sell the services, you know, or is it the strategic level? Is it board? You know, but actually, in many large organizations, you know, there’s kind of maybe some silos and even potentially politics, as well. But actually, we reached a point where it was so obvious that it needed to be done. The technology, the hardware was reaching a price point and it was realistic to actually deploy on large volumes, and then obviously, we get the large volumes of data and that gives us a chance to create all sorts of interesting insights and services. And what you really want to do with that data is you want to understand the causality of things. So for example, this is the one that we’ve deployed on rail cargo wagons. This is called the Globehopper 3. We have already 200,000 of these devices deployed on one of our customers. So we’re gathering 1.8 billion data points a month already just from those 200,000 devices. And obviously, now we’re deploying millions of devices with our new customers and our new clients and deployments. Now this is the next one that we announced the other day. We’ve done a deal now with Knorr-Bremse to monitor brakes and HVAC systems on all of the trains in the world. But the point is, I mean, one of our customers, they were good enough to give us a rail car that we were able to smash up for a few weeks. There were no shortage of volunteers from amongst our techies for this project. So we covered the rail car in sensors and we dropped things on it and we derailed it, and we shunted them together at excessive speeds, and we really trashed it. But through that experience, we were able to do supervised machine learning onto our algorithms, and we were able to actually distinguish the cause of the impact. If you know 3 g happens, it’s almost irrelevant if you don’t know what made it happen because you can’t automate any process. So if a crane driver’s dropping things regularly onto a chassis and it’s damaging the springs and the bogie on the rail car, then you need to train the crane driver. But if it’s the shunting yards where they’re, you know, they’re lining up the trains and making the compositions and they’re hitting it from another direction, then it’s a different outcome. You know, you might need to change your service level agreements, or I don’t know, something. Also, you might want to send that data to the insurance team to make claims. So, you know, there’s lots of different possible routes for that data to create the value. But you need to have context around that data, and that’s about having big data and also integrating the domain knowledge from the expertise in the industry.

– [Ryan] Fantastic. So let me ask, obviously, throughout the development of the solutions, the implementations of the solutions with different customers, there’s different components, right? There’s a hardware, there’s a software, there’s a analytics piece. All of this is needed for kind of the overall value creation for this. How do you handle those conversations, and what kind of advice do you have for people out there on how to kind of go about selecting the right piece for each of those components for the whole thing to kind of have its best chance of success?

– [Daniel] Yeah, so I mean, we had a really interesting experience, and we learned really by doing and by asking the questions, as I said at the beginning. And do you know, actually, when you ask the client often, you know, it’s like the Henry Ford story. He asked people what they need and they said, “A faster horse,” you know, there’s a famous story. They couldn’t imagine a chassis with a combustion engine and a steering mechanism and the braking and so on like Henry Ford and his engineers could. So, you know, actually, we have to go to the clients and we have to ask them about their operations and where they’re having problems. And actually, when we first started, we said, “Well, we’ll build IoT hardware, energy harvesting, zero maintenance, you know, long life hardware, and we’ll sell that hardware.” And then we realized actually it’s not so simple. The customer said, “We need to see something. We’d like to see dots on the map.” And then we said, “Okay, well, we’ll build the front end to where you can see those dots on the map.” But then we explained that you actually want to integrate that data through APIs into your control systems and transportation management systems. And then we looked at those together with the customer, and we realized that they were quite, you know, old and maybe, you know, these sort of legacy systems, and you need to start again. So then we started to build the platform, and everybody claims to have a platform these days, but you know, what does your platform do? And what does my platform do? And it’s words like “end-to-end” and “transparency.” And, you know, so actually you need a support from a vendor who can supply all of these integrated aspects. So, you know, it goes from sensor to gateway, then into device management, data management, obviously it needs connectivity, and then it’s into the business process automation through the analytics, through the big data, and through the machine learning, and so on. So you need, really, an integrated solution. And it has to be, you know, bulletproof from the hardware side all the way through to the data processing side. So my advice to anybody is to work with a partner. It needs to be a partnership, and you need to be collaborative, and you need to share ideas and data. And this is a big challenge because, you know, working across the organization, you know, to remove those silos, everything needs to be integrated in a holistic way.

– [Ryan] And when it comes to the like domain kind of expertise that is required for these to be successful, how important is that for a company looking to adopt a solution to find within a potential partner? Or is it something that you feel is in a sense learnable from the initial engagement onward? Because obviously, understanding the industry, understanding the details of that particular use case solution, even end user and the problem they’re actually asking you to solve is super important, but how do you kind of view things from there?

– [Daniel] I think, again, it’s about having a very close relationship, a very trustful relationship. It’s about understanding the client, and it’s about understanding their business. You know, like for example, a leaser of mobile supply chain assets has a very different mindset to, you know, sort of an operator, because, you know, the maintenance is on them, you know, maybe in both cases, but they don’t see the assets so often and they don’t have such control over it. So, you know, it moves into the business decision making, you know, sort of into the product life cycle managements and so on, and then you need the domain expertise from the client, and that’s about communication. And I think that, to be honest, you have to really not make any assumptions. You have to treat each, you know, business case or use cases, you know, uniquely, and you have to really unpack what’s going on. You know, a lot of these sort of older, more traditional industries, they’re losing that domain expertise as people retire. You know, you’ve got people who’ve worked for the organization for 40, 50 years, and then, you know, if you lose all that knowledge, it’s really brutal. So you have to build cross-functional, interdisciplinary teams with our techies, our, you know, sort of application consultants, and also with the client from a strategic point of view, but also, you know, the guys who are working on the tracks, they’ve got a gut instinct for things. And it’s very interesting when we get and unpack the data and we start looking at that data together, often we’ll have this conversation. Somebody will say, you know, “I knew that was happening, but I could never prove it before.”

– [Ryan] Absolutely. Yeah. It’s interesting, ’cause I also think there’s another element to it that we don’t talk about a lot is not just the implementation pieces and kind of what this enables organizations to be able to do, what problems it allows ’em to solve, but there’s the business model element, too. And I’d love it if you could touch a little bit on kind of what IoT, big data, especially in the supply chain space, has enabled when it comes to new business models for kind of any of the stakeholders that are involved.

– [Daniel] So, okay. That’s a great question. First of all, I’m gonna just tackle the topic of transparency, because we’ve got data aggregators out there who are promising transparency, but obviously, it’s nothing like the transparency that comes from real-time asset and cargo level, you know, sensor data, active sensor data, you know? So if you are taking, you know, port turn and turnout times, and you are basically crunching that and making, you know, sort of ETA’s, it’s not as good as a dynamic ETA that comes from our live hardware, but obviously, transparency’s almost a double-edged sword because you’re exposing yourself, as well. So you have to make sure that you are taking your business responsibilities as an operator or as a supply chain participant, you know, very seriously if you’re gonna go the route of transparency, because, you know, there might be more insurance claims or people start to question demurrage or things like this. And the truth is that, you know, if you have those, that level of visibility, and it’s empirical and you can rely on it and you’ve got, you know, like I said before, you know, you’re actually getting business intelligence that’s actionable out of it, then you are able to transform your relationships with your partners because everybody else needs a part of that data. So, you know, you are able to renegotiate your operating model or your participation, and you’re able to charge more people for the digital services, then maybe you had an original customer with somebody who wants to move something from A to B, and now all of a sudden, you’re supplying 20 different parties with services that come about because of that data. So really, it gives you a field day to think again about your business and to change your business models and to start even charging for outcome-based economics. You know, so you get paid per outcome and you’re able to actually, you know, prove that you’ve contributed value. And actually, I think this is a very interesting point, because, you know, the supply chain is hemorrhaging value. The important thing is to actually know who’s creating value and to distribute the share of wallet according to who’s really created and acted on that value. So I think we’re entering a very interesting phase because as the data starts to become something that’s real in volumes, and consistency, and quality that is needed, then the IP starts to happen on the business model generation. And I would recommend to read the Osterwalder book, “Business Model Generation,” and to play around with the business model canvas, you know, for companies that maybe have never done that before, because if they could see themselves as a traditional supply chain player to start to reimagine, you know, where they can distribute that value and how they can monitorize it.

– [Ryan] Absolutely. It just opens up a whole kind of spectrum of potential for these organizations to grow, to be more efficient, to generate more revenue, grow their business, you name it. And it’s super fascinating to kind of see how IoT from a technology standpoint is doing this across lots of different industries, not just supply chain. Like it’s happening across many different industries on a daily basis. I did wanna ask you, though, as it relates directly more towards the supply chain side of things, what are some of the biggest challenges that you’ve seen companies face with the adoption, the implementation of IoT, and kind of advice for how to kind of overcome them aside from what we talked about earlier, which is making sure you’re picking the right partner, finding the right integrators, the right components, and things like that, but just generally speaking, what other challenges are you seeing exist in the space that are really important for people to kind of take note of?

– [Daniel] Yeah, so I would hone in on one particular one here. And I think that this is really important, and a lot of people talk about it, but, you know, I think it’s still important to talk about it. It’s the culture. It’s actually transforming your mindset to start to deal with your business from a data point of view. And to start to also look at, you know, building internally, cross-functional, cross-disciplinary teams. And, you know, in a way, rail hasn’t changed much, for example, for over 100 years or 200 years, but it was the backbone of growth, you know, for the North America, and everywhere really. Industrialization was built on it, but it became kind of uncool. And, you know, obviously you need to attract new talent, data mindset, you know, digital talent into these industries. And you have to embrace that, but also make sure that you treasure those domain expertise and you don’t cast them out, but you actually treat them with great respect because obviously it’s that combination of the two that needs to be, you know, present in order to make this really happen. So I think in the culture, you know, there’s a lot of people maybe talking about IoT, and talking about data, and talking about digitalization, but it’s to actually take it very seriously, and to invest in it properly, and to take it from a strategic point of view, and to make sure that your organization, and your communication, and the way that you work together is not siloed thinking. Not building, you know, empires within the organization, but it’s integration of different mindsets and cultures to make the most of the opportunity.

– [Ryan] Absolutely. Yeah, that’s a great way to kind of put it. And I think you’re seeing that same thing, that cultural transformation, that old-school versus new-school, just the general way of thinking needs to evolve. And it’s a challenge in any industry. I mean, you have a lot of champions within organizations bringing IoT technology and solutions, excuse me, into the company, but they’re running into other individuals within the company who have an older way of thinking who aren’t really looking at these in the right light in order to see what they truly are and the value they provide for organizations. And it’s until that really shifts across the organization, it is a roadblock for adoption and something that definitely needs to be considered before you venture on that path, for sure.

– [Daniel] Yeah, definitely. I think there’s some fear as well, because you know, it’s a fear of change and the fear of things, you know, big data is quite a hard thing to understand if you haven’t grown up in, you know, sort of a digital age or, you know, if you haven’t studied it. And I think, you know, I think that there, again, it’s about these cross-disciplinary teams and to understand that we have to do it together.

– [Ryan] 100%, yeah. Doing it together is kind of the biggest thing. Like you mentioned earlier, partnerships. It’s just critical to how important partnerships are for the success of these solutions to get out there. As we’re wrapping up here, I wanted to ask you for our audience who is kind of interested in learning more, follow up with questions, kind of learn more about the company, what you all have going on, what’s the best way to kind of stay in touch and kind of follow along?

– [Daniel] So our website’s evolving a lot at the moment. I know a website seems like an old-school format these days, but actually, you know, it’s still something that’s, you know, a very valuable tool. And we know, obviously, also I have my own podcast. It’s called “The Wise Machine.” It’s probably not as mature as your product, but it’s is getting there. And also, I’m speaking at conferences and events, so just keep a look out on LinkedIn and so on. But overall, we are super active. We are traveling all the time and, you know, we are really working with some of the biggest organizations in the world. And I think that, you know, I’d encourage everybody who’s interested in this topic to understand how it might, you know, improve their own supply chain or how they might be able to iterate and change their own business models to, you know, evolve to meet this new opportunity and, you know, just to sort of keep tabs on it because it’s changing so fast. And when you think about it, you know, really, nobody could have imagined even 10 years ago that over a million dry shipping containers would get equipped with hardware. And you know, now in a way it’s strange, because rail was the first, and, you know, you think that probably air cargo and things like this, you know, sort of are quite advanced, but actually, it’s quite difficult to put this whole thing together. And also, it needs to be the right moment in terms of, you know, the buying power from the market, too. So, you know, previously, freight rates were in the ground, and now it’s booming again. So you’ve gotta take that money and invest it when you’ve got it and make things happen as quickly as possible. But also, you know, with a roadmap that makes sense to include partners and other participants, and to start thinking about your competition maybe needs to be reconsidered. It’s maybe “co-opetition.” You cooperate with your competition by sharing data, because you know that when something is not actually shared, then you have an issue that actually, as soon as it’s out of your hands, then the inefficiency kicks in again and all the benefits that you’ve improved, you know, your own systems, actually, you lose it when it’s out of your hands.

– [Ryan] Very well said. Absolutely. Well, Dan, this has been a fantastic conversation. I appreciate your time. I know you’re traveling, and speaking, and doing tons of stuff, so making time for us, it means a lot to us, and to me and our audience. So really appreciate your time. I know I’ve spoken with other members of your team about doing some more content together around solutions and other types of other topics that we think are really important that you guys would be great to kind of speak to. So hopefully we’ll have a chance to talk again and find other ways to work together.

– [Daniel] Thank you so much, Ryan. And thank you for the questions as well, because I think that was really on point, and, you know, I think you brought the best out of me, so thanks very much for that.

– [Ryan] Absolutely. But yeah. Thank you again, and we’ll hopefully talk soon.

– [Daniel] Excellent. Cheers, Ryan. Thank you.

– [Ryan] All right, everyone. Thanks again for watching that episode of the IoT For All Podcast. If you enjoyed the episode, please click the thumbs up button, subscribe to our channel, and be sure to hit the bell notification so you get the latest episodes as soon as they become available. Other than that, thanks again for watching, and we’ll see you next time.

https://www.iotforall.com/podcasts/e208-iot-big-data-in-the-supply-chain

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