IoT Leaders: 3 IoT Predictions for 2021 & Beyond

Podcasts

In this episode, we interview Nick Earle, CEO at Eseye, about three of the top 10 predictions for IoT in 2021 and beyond.

What we talked about:

  • A story of data possibilities featuring a smart vending machine
  • Why hardware skills will be even more important in the near future
  • Experience is enabled by data
  • How the 3 predictions are interrelated

Get your copy of 10 IoT Trends to Watch in 2021 and Beyond, as mentioned during the podcast:

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Transcript

Intro (00:01):
You’re listening to IoT Leaders, a podcast from Eseye that shares real IoT stories from the field about digital transformation swings and misses, lessons learned and innovation strategies that work. In each episode, you’ll hear our conversations with top digitization leaders on how IoT is changing the world for the better. Let IoT Leaders be your guide to IoT, digital transformation and innovation. Let’s get into the show.

David Langton (00:31):
Welcome to the IoT Leaders Podcast, with me your host, David Langton. And for today’s episode, we’re going to do something a little different. So, the main podcast host, Nick Earle, the CEO of Eseye, has jumped into the guest hot seat today. Hi Nick, good to see you. Thanks for joining us.

Nick Earle (00:48):
Hello David, good to see you. Glad to be here.

David Langton (00:51):
Great. So Nick, I remember sitting down at the end of 2019 with you to talk about what was going to be the inaugural predictions report for IoT that we published. Now, no one could have predicted what was going to happen in the world last year, it’s certainly been an interesting 12 months. But it’s fair to say I think some of the predictions were, you know, we certainly saw them playing out during the COVID experience and that whole situation. So I thought, obviously we just recently published the latest report on predictions for 2021 and beyond. And although there are 10 of the predictions to go through, there’s a lot to go through, I was very keen to see if we can drill down on some of the key predictions that you think people should be watching out for in the next 12, 18 months. So perhaps with that, you can kick off with the first of those three predictions, Nick.

Nick Earle (01:44):
Yeah. Thanks David. And as you said, it has proved very popular. Predictions is a difficult business to be in, and we certainly don’t claim to know all the answers and we certainly didn’t predict COVID. But we are seeing an acceleration of some of those predictions as a result of COVID. So what I’m going to do perhaps is pick three of them, and all 10 are interconnected. So to some extent, each one is interconnected to the other one. But the first one that I want to talk about is the, what is going to be possible in the world of data. And as we all know, I mean, the whole reason for doing IoT is to get data. Data, as they say, is the oil of the new economy. Nobody wants a smart device, they want the data from the device.

Nick Earle (02:27):
But other than just say, there’s going to be a lot more of it, I mean, we all know that’s true. And data itself is going to be cheaper, we also know that’s true. I think the way to look at this is to go deeper and say, what is the data doing to value chains? And the bottom line is, what we’re seeing is a significant disruption of value chains via a transfer of power to the end user, with an associated dissipation or weakening of the power of the brands of large companies. Now, there’s a lot there, so let’s try and unpack it. With IoT, it’s all about creating a new experience for your user, your customer, if you’re a business. Or it’s about creating a new business model that wasn’t possible previously. And what we’re seeing is some areas where this is really, really accelerating and it’s having a fundamental effect, as I said, on these value chains.

Nick Earle (03:23):
So let me make it real and talk about the first of the two, which is in vending machines. Now, vending machines have been around for ages, but what’s happening now is you’re getting smart vending machines. Smart vending machines are being built around a personalized experience. So in one of the podcasts will be Costa Express. Costa Express with their vending machines, they call it a barista without a beard. Now, it’s not just a snazzy marketing phrase. What they’re really trying to describe is a personalized experience to every individual customer delivered through a machine. And so what’s happening is that they’re recreating a personalized experience that’s much better than, for instance, getting your name written on the side of a cup. But it’s not just that, they’re also delivering it without having to have shops. The Costa Express machines are not found in Costa shops, they’re found in other people’s premises.

Nick Earle (04:17):
And what they’re doing is they’re data mining your experience, what you’re doing, the choices that you’re making on the types of coffee, the additives you put in the coffee, when you have the coffee, is it a small coffee, a large coffee, et cetera, et cetera. They’re data mining that and actually then using it to proactively offering you differentiated services. So the machine, the screen reconfigures itself, or they send you messages, they link to you via the app that gives you your loyalty points so they know who you are. So if you think about that as an example, not only are we now saying, well, you’ve got the person who makes the coffee interacting directly with the consumer without, in this case, one intermediary step, which is the retailer. But secondly, what you’ve got is you are actually applying the principles of internet 1.0 to IoT.

Nick Earle (05:09):
Because if you think about, when the internet first came out in the ’90s, it was first of all talked about as a set of technologies. It was all about HTML and web browsers and things like that. But then we pretty, after about two or three years, we said, oh, no, no, no, no, no, what it’s actually doing is enabling you to buy your own airline ticket. It’s enabling you to buy a book online, to book a hotel online. So there became this massive disruption of business models and collapsing of value chains, connecting the person with the product more closely to the person who wants to consume or buy that product. But all we were doing is really data mining one element of our behavior, which is our, as consumers, interaction with a digital service. In that case, amazon.com or Airbnb or United Airlines.

Nick Earle (05:58):
What we’re now seeing is the opportunity to data mine our interaction as human beings with billions of physical things, not digital sites. So as more and more physical things become connected, we actually now can see an exponentially large capability to use that data to create new disruptive business models to disintermediate supply chains and deliver previously undreamt of experiences. Now, let me try and bring that together with my second example, which is what’s happening in healthcare. And this has definitely been accelerated by COVID. So, the traditional value chain or supply chain, if you like, in the health industry is this, I don’t feel very well, I self-diagnose myself. Maybe it’s a few days and I suddenly realize, I’ve not been feeling great for a few days, I’ll phone up my doctor, I’ll wait to get an appointment.

Nick Earle (06:56):
Okay, now I can get it over the phone or over video, whereas previously I had to go to the doctor. But if I want to go and see a specialist, the doctor has to approve it. He or she has to recommend the specialist. I need that recommendation in order to then phone up the other party, which is the insurance company, because, have you been referred by a doctor? I go and see a specialist. Yes, you definitely look ill, I’m going to do some tests. Got the test, send it to the clinic, the clinic does some tests. And let’s say I get to the end of that, I feel better, I go home. And then it’s up to me, if I then start having those symptoms, I have to start the process again. Now, we all know about that. And it’s different in different parts of the world, but essentially it’s the same process.

Nick Earle (07:35):
What we’re seeing now with IoT is people producing this new phase of healthcare wearables. These are very advanced pieces of specialized hardware that interact with our skin and what’s happening in our body, and also other devices that are in the home. And the data doesn’t go to your GP, the data goes to a company that you’ve never heard of. It’s a company that actually uses artificial intelligence to actually analyze what might be going on in your body. And they’re accessing data from institutions at the far end of the value chain, like the Mayo Clinic, or like university teaching hospitals. A good example of this is a company called Biofourmis, who are doing exactly this. And their goal is to actually prevent disease from happening in the first place. And they’re not just actually completely disintermediating the traditional supply chain of healthcare and offering you choice as a consumer.

Nick Earle (08:30):
But what they’re doing is, they’re actually then working with the pharmaceutical companies so they can actually create drugs for the conditions that they’re seeing happening real time. Now, obviously this has huge implications on the current environment like COVID and things like that, where you wear a wearable and you could get advanced notification of symptoms, especially given that one in three people can be asymptomatic. So what I’m trying to say in the prediction, David, is that it’s not just that data will explode and petabytes and zettabytes, we know all that. But actually, the data is going to completely change the competitive landscape for companies. And that’s really where we as an IoT company with 2000 customers say to customers, you should really start, first of all, by thinking, can I be disintermediated? Or what is the experience to the consumer I’d like to deliver? Or can I use this as an option to collapse the value chain?

Nick Earle (09:33):
Start there, think about what needs to be done. And then from there, decide what data you need to measure. Don’t just capture data for data’s sake. And this disruption, the ability to mine people’s interactions with physical objects rather than digital websites is going to be a much bigger disruptive catalyst than the first wave of the internet was starting off in the early ’90s. Because now we’re talking about 50 billion things, not just a few million websites. We’re not just talking about monetizing your search behaviour. So big, big changes are coming and the smart companies are starting … they’re thinking here on IoT, not just thinking, how do I get connectivity into a device, or how do I collect data and then decide what to do with it.

David Langton (10:23):
Well, that’s a pretty good start. So with all of this data, and we talked about big data, so I remember 10 years ago this surely is going to be going into the realms of potential massive data. I mean, data is going to be created from all these devices and products all around the world. So I’m sure this has implications on a wide range of data processing, data analytics and other technology applications. But what are the implications for the IoT devices themselves?

Nick Earle (10:57):
Well, it does have massive implications for the IoT devices, because if you take that approach to say part of it is about creating a new disruptive business model or a defensive business model against a disruption if you’re the incumbent, or delivering a previously unimagined human experience. And I would argue that Netflix was a previously unimagined human experience, if I’d have told you about it in 1998. You then say, well, what does the device look like? And you suddenly realize, well, it almost certainly doesn’t look like an off-the-shelf IoT device. There are millions of IoT devices you can buy; trackers, medical devices, off-the-shelf, put a SIM card in it, and you’re connected. But that delivers a generic consumer experience. It’s not a differentiated consumer experience. So what we find the leading company is doing is that when they actually start off with imagining the art of the possible of what they could create, they then say, okay, well, what type of hardware would I need to do that?

Nick Earle (12:00):
And remember, we’re talking about really edge aggregation devices that not only have logic in them, they’re programmable, they have logic. But also, they communicate with multiple sensors like the healthcare device that I was talking about. So what you very rapidly realize is the device is actually unique to the use case. I mean, the Costa Express coffee machine I talked about, people think it’s a coffee machine and of course it is, but that personalized experience that you get, the barista without a beard, is enabled by 90 sensors inside the machine. And it’s been custom designed to deliver that experience. And it’s got an edge aggregation device, in this case provided by us. So when that light goes on, you then start thinking, okay, so truly great IoT requires custom hardware. And at that point, the blood starts to drain out of people’s faces. Because if you think about it, I’ll go back to my late ’90s and Marc Andreessen brilliantly, what he was doing at the time. But he’s become famous since then for a whole variety of things.

Nick Earle (13:09):
And one of them is a phrase that everyone repeats, which is, “Software eats hardware.” It’s not about hardware is old fashioned, it’s, you don’t get it, it’s all about the cloud, it’s all about SaaS. But actually, when it comes to IoT, it’s the other way round. It’s actually all about hardware. As I said, we’ve got, as you know, 2000 customers, 80% of those customers came to us because they had a failed IoT project. And by far and away, in excess of 80% of that was to do with hardware that didn’t do what they meant it to do. Because it’s called hardware for a reason, it’s really hard. I mean, people don’t even want to know what the questions are, nevermind the answers. How would you get the firmware settings into the modem so that the battery doesn’t get drained in case the tower is further away? Because, did you know, it pings the tower seven or eight times if it’s further away than if you’re right next to the tower? People don’t want to even think about those questions.

Nick Earle (14:06):
How do you actually design the sensors in such a way that you only collect a certain amount of data, and which data do you back hold and how do you get your devices certified onto mobile network operators? Oh, and by the way, it works different in the US than it does in Brazil, than it does in Europe. And people are saying, I didn’t want to get into hardware design. So if the hardware really is fundamental to delivering the experience, the big question is, who creates the hardware? Who designs the hardware? And right now, it’s a massively fragmented ecosystem. There’s lots of small boutique hardware design companies, and some really big ones that make things like mobile phones and whatever. But those mobile phones have millions of dollars being spent on them to deliver that incredible tightly coupled hardware and software experience. So when people are considering, as enterprises, IoT projects, one of the questions they have to ask themselves is, how do I get my hardware designed around the use case?

Nick Earle (15:05):
Because if I get it wrong and it doesn’t work, I’m going to have to go back to the beginning. And then my business outcome collapses, and I probably won’t get a chance to have the second bite for the project the second time round. That’s one of the reasons why, as Eseye, we’re not the only company that does this, but there are very few that do. That’s one of the reasons why we actually spend a lot of time doing hardware design, as well as connectivity. And we work with our customers and people who we hope to be customers in the future to actually say, what experience are you trying to deliver? Let me make you a prototype of the hardware in order to show you the art of the possible with regard to the experience. And as I say, there are a lot of companies out there, but we really push the fact that you do need to think about hardware.

Nick Earle (15:54):
It’s not a catch-22 because it doesn’t mean you have to be hardware experts. But when you start your IoT project, step one, do the imagineering that I talked about in the data, the disintermediation of the supply chain, the delivery of a previously undreamt of consumer experience. Number two, then think about, how can you actually create the hardware to deliver the experience. And unfortunately, that probably means some degree of custom work. But the work that you do up front in the hardware design phase actually pays for itself many, many times over when it comes to the delivery of the business outcome and the speed at which you can deploy the devices. And so that is one of the biggest factors why a lot of surveys out there say between 70 and 80% of all IoT projects fail, because often they fail on the thing that everybody thinks is the easiest of all, which is, well, it’s just the device. There’s loads of them, thousands of them, I can just buy them.

Nick Earle (16:53):
But actually, it’s not as simple as that. It’s not like the cell phone. And so the second prediction is all about the fact that those with hardware skills and those that can design the business case around the experience will actually rise to prominence as we go forward, simply because there is no alternative than to design the device around the experience.

David Langton (17:14):
That’s a great point. And I think, as you say, I think something we’ve heard a lot, many times is, perception here is key. Isn’t it? About the device. We’ve heard customers say many times about, well, isn’t it just so easy? You just put a SIM in the device and it’ll just work. Well, I think you’ve just highlighted, Nick, no, it’s not that straightforward. It’s much more complicated than that.

Nick Earle (17:33):
Well, it comes back to the fact that millions of dollars that are spent by Samsung and Apple, in fact, hundreds of millions of dollars. When you’re designing your own IoT device, you don’t have that budget or those skills. And so, no, it is a very difficult area. But fortunately, one day it won’t be as difficult, it will be able to be stripped down to silicon. And we’ll talk about that in another prediction. Ultimately, this will all be features of silicon, but right now it isn’t, which is why this area is so important. And so that’s the second area.

David Langton (18:05):
So moving on to the final prediction, perhaps you can give our listeners an example of where these two things might come together in the future. So fusing the data and the hardware and where that might lead us. What sort of examples might we see in the future? What areas are going to be big?

Nick Earle (18:22):
Yeah. So this third area is one that I think is going to play out over a little bit in 2021, but a lot in 2022. And in 2023, we’ll all look back and say, oh, it’s so obvious, I always knew that was going to happen. But I’m actually going to approach it in a strange way. I’m going to approach it by talking about the difference between linear and exponential models. And the basic premise is that as humans, we’re programmed to just not understand an exponential trend. And let me give you two simple examples. If I said to you, David, a man walked 16 steps and each step is a meter in length. The question is, David, how far away is he when he’s done 16 steps? So how far away is he, David?

David Langton (19:04):
16 meters.

Nick Earle (19:05):
Well, you’re a smart man. Well done. Okay, a man walk 16 exponential steps, one, two, four, eight. How far away is he from you after 16 steps?

David Langton (19:16):
You’re testing me now.

Nick Earle (19:18):
And you don’t know, and nobody does. And I don’t either. But the answer is, he circumnavigated the world several times. And the point about it is that disruption is inherently invisible when it first starts. And let me give you a practical example of that. Because a lot of technology advances exponentially, Moore’s Law, whereas progress in traditional business models advances linearly. Because what we do is we try and take 5% of cost out a year, that’s seen as a success. So the best example, very, very well known is Kodak invented the digital camera and the digital camera killed Kodak. The digital camera, when it first came out was, I don’t know, it was 50/60 pounds in weight. It was as big as a desk, a small fridge. It had like, I don’t know, an eighth of a pixel and it seemed like a really stupid idea.

Nick Earle (20:10):
And after a couple of years, Kodak killed it because they were in everything. They were vertically integrated from chemicals to film, the processing, the cameras and everything else, the Kodak moment. Of course, in retrospect, we can now see that if you look at every single component of that digital camera, it was following Moore’s Law exponential curve. And so eventually it would kill the thing that was the accepted knowledge at the time.

David Langton (20:36):
And so, what’s the relevance of that in terms of the third prediction?

Nick Earle (20:41):
Well, the third prediction is to do with disposable IT. IT that IoT devices actually, disposable IoT devices that cost just a few dollars, you use them and you throw them away. And if you could do that, if you could create a disposable, almost print an IoT device, then what you could do is start applying this to some major, major problems that today are huge issues for the world, but have just been impervious to this, such as food distribution. So let’s take food distribution, or you could say COVID vaccine distribution, it’s chilled food, but let’s take food. Food that goes off over time, 30% of all food is thrown away. And that’s a very, very complicated problem. Multiple reasons why. But one of them is lack of supply chain visibility. You don’t know when the food is going out of temperature range and also it can be in the supply chain for too long, so it’s gone past its sell by date.

Nick Earle (21:39):
We’ve tried to solve this as society, this huge problem. Over production of food at one end, which has issues to do with carbon gas production, especially if it’s meat and the farming, through to not enough food on the consumer end, or people throwing things away in their fridge because they just bought too much. So what is happening is that people are saying, well, hang on a second, you can actually now, due to advancements in multiple areas of technology, like the ability to print a battery, or you can print a circuit, you can print sensors because the sensors is a circuit. Now you can’t quite print a modem, but the cost of the modems is coming down very, very significantly. They’re getting really slim, like a small scrabble piece. So now we’re into, what you’re starting to see is the emergence of the first generation of food labels. Food labels that can be attached to every box.

Nick Earle (22:33):
We’re not talking about the Mars bar wrapper yet, but let’s just say every box of crabs legs or whatever. I mean, up to 20 boxes of crabs legs in a large box, attach a food label to a box. If that food label was five or $6, which might be the target price we could see within six months, you could then do real time tracking of the box, both location and temperature. And either intercept the box or just basically have visibility of your supply chain. So the idea is that you print the label when you create the box, you put the label on the box, you monitor it. I’m not talking about some of the early versions that use things like LoRa, which actually required specialist hardware and you could only measure things when the box went past the hardware. I’m talking about ubiquitous global cellulous or 100% coverage of cellular across multiple countries, which of course is one of our key value propositions, but some other components of this technology are important as well, particularly the printing side.

Nick Earle (23:35):
And then what you can actually do is that if the box gets too warm or whatever you intercepted and you know where it is, once the box gets to its destination, by opening the box, you break the circuit. By breaking the circuit, you throw the tag away. Then what we’ve got to do still is get more advancements on the issue of not creating too much waste as a result of this, which is the recycling issue of these principal devices. So we need devices that compose, if you like, over a period of time, and the technology is still lacking in that area. That’s why I think it’s going to be a 2022, 2023 thing, but there are multiple developments happening in all elements of what I’ve just talked about. And I think the first devices are really going to be in the market in 2021.

Nick Earle (24:20):
Now, when you do that, you then start addressing some major, major societal issues like eliminating up to 30% of food in the global food supply chain. So now what we’re seeing is, IoT moves beyond traditional IoT where we’ve predicted for years there’s going to be 50 billion things by 2020. Of course, we missed that. That prediction, as an industry, that’s another subject we cover in a podcast. But we’re now going to what’s being called massive IoT. Massive IoT is the 500 billion things and food tag tracking or vaccine tracking or whatever you want to call it, it’s one of those. As all the prices … and of course the data is another element. The data pricing are coming down, everything’s coming down. It’s the Kodak principle, that everything is coming down. So it will be possible, just not quite yet, but we’re getting very close.

Nick Earle (25:17):
And then what you then get is saying, oh, well, that’s amazing. But we’re not going to stop there because then what will happen is ultimately you might get down to 50 cents. And it’s not crazy to think that in this decade you get down to 50 cents or 40 cents or something. And then you can start thinking about putting it on a product, an actual product. A chocolate bar or the actual individual box of food or food itself. Then you’re into, I don’t know what we’ll call it, massively, massively IoT or infinite IoT. So the point about the third prediction is, it’s different to the first two. And that we’ll start to see the first pilots of this in 2021. They won’t be ideal because we still got some major technical issues to deal with, but actually what that will do, if I link it to the first two predictions, is that it will give rise to some new super aggregators.

Nick Earle (26:12):
So to finish it off, it’s not just a technology prediction. When the first wave of the internet happened, and I know from my experience, I was over in Silicon Valley at the time and we didn’t really understand. Amazon was a bookseller. I say in one of the podcasts, as you’re aware, I was lucky enough to actually spend time with Jeff Bezos in 1999. I wish I’d been smart enough, I would have bought a lot of stock, I didn’t. But I asked Jeff Bezos the question, “What’s next for Amazon?” And he said, “I’m going to be the biggest retailer in the world.” And I just thought he was a nut job.

David Langton (26:47):
Crazy.

Nick Earle (26:47):
Because he was a bookseller. He was just going into DVDs, digital products. He said, “No, everything.” I just thought … I mean, the iPhone was eight years away still. But he became a super aggregator of what he is now. But the other thing that he’s done is he has this incredible track and trace facility. I know where my Amazon parcel is going to be delivered. Amazon Prime, your parcel will be delivered in the next minute. And then if you look at Uber, I never thought Uber would happen, aggregated. A disaggregater of the traditional supply chain. But that little app which shows where the Uber car is, and if it’s a black car, it shows black and if it’s a red car, little red car. In the UK, our food delivery here, Deliveroo, has exploded in popularity, but I can see the little motorbike and where it is. I can open the front door as the Deliveroo person is walking up the steps.

Nick Earle (27:41):
And so the ability to offer real-time information about where a product is, is actually a massive differentiator in your choice of that product. The experience is more valuable than the product itself. The experience is enabled by the data. So as we get into massive IoT, there’s going to be the rise of super aggregators. In the same way as here in the UK, companies like Ocado said, “I can give you an Amazon type warehouse experience, why are you trying to do it yourself? Outsource it all to me and I’ll do that whole warehouse thing for you because you’re not good at it, I am.” So, business process outsourcing. I think the logistics tracking area, real-time tracking of physical product as it moves around the world, it doesn’t have to be food, anything, is going to give rise to a series of super aggregators who sell information about where assets are to their customers, as opposed to selling physical products.

Nick Earle (28:43):
In fact, it’ll be more profitable to give the products away for free and sell the information about where the products are, especially if you’re doing B2B, than it will just to sell the physical product. And so, large companies will, as always, try and do it themselves, but there will be the rise of these super aggregators using real-time track and trace to outsource supply chain management. And that’s definitely starting now, but it’s going to explode as we follow Moore’s Law down and as we see massive IoT. And who knows what will happen when we start talking about trillions of devices in the future. Your brain hurts just to think about it.

David Langton (29:23):
Mine hurts. Yeah.

Nick Earle (29:24):
Yeah. Just to think about what happens when these things become tiny, tiny, and they’re in clothing or whatever. So I think that’s what we’re going to see, and it’s linked to the first two because it’s all to do with the product, designing the product for the use case, and it’s to do with the value of data and the relative value of data to the physical product. In this case, to either eliminate waste or to sell the information to business customers about where their products are, because you know more about where their products are and they know about where their products are. So very, very exciting, as always, in the world of IoT. Lots of predictions, all interconnected. And that was just an overview of three of the ones that we know are popular from the number of downloads that we’ve had off the set.

David Langton (30:11):
That’s great, Nick. And yeah, it’s quite, as you said, mind blowing to work out or trying to foresee where this all going to go. I’m sure it’s going to have some twists and turns along the way, as these things always do. But yeah, very excited to see how it all plays out in the next 12, 24 months. And I’m sure our listeners will be eagerly trying to look for this report to download. And just so I can point them in the right direction, where you need to go to download is at eseye.com/2021predictions. Or you can also email us at iotleaders@eseye.com, that’s E-S-E-Y-E.com. And we can get a copy straight over to you. So yeah, it’s going to be a big year for IoT, a big couple of years coming up. Who knows what’s going to happen? But I’m sure we’ll be tracking this and following this closely as we go. I’m sure there’ll be lots of podcasts coming up in the next few months and coming years, Nick, on this.

Nick Earle (31:06):
Yeah, we will. And that’s a good point to finish with, David. Yeah, the people, the guests that we’re inviting on the shows … and that’s where we always say, if you think of anyone that you think would be good to interview on these shows, then please let us know via those contact details. But we’re interviewing people about their thoughts of where this will all go and the best practices that they see and perhaps what not to do, what’s working, what’s not. We’re trying to just be a guide for people around this world. Which is what everyone says, please demystify it, make it less complex, give me some advice. So that’s the gap we hope we’re filling. And each podcast deals with one little element of all of this and goes deep. And so I hope people enjoy them. Certainly we’ve enjoyed making the ones that we’ve made so far.

David Langton (31:51):
Absolutely. Yeah. So for more insights for our listeners, please do subscribe to the IoT Leaders Podcast, and we look forward to you tuning into future episode. As Nick just alluded to, lots of exciting things to come, and hear about all the exciting things or interesting things happening in the world of IoT from all these leaders and disruptors who are really pushing for the boundaries around digitalization. So thanks, Nick. We look forward to hearing from you soon on another podcast when you’re back in this seat.

Nick Earle (32:19):
Okay. Thanks David, and thanks everyone for listening.

Outro (32:23):
Thanks for tuning in to IoT Leaders, a podcast brought to you by Eseye. Our team delivers innovative global IoT cellular connectivity solutions that just work, helping our customers deploy differentiated experiences and disrupt their markets. Learn more at eseye.com.

Outro (32:44):
You’ve been listening to IoT Leaders, featuring digitization leadership on the front lines of IoT. Our vision for this podcast is to be your guide to IoT and digital disruption, helping you to plot the right route to success. We hope today’s lessons, stories, strategies, and insights have changed your vision of IoT. Let us know how we’re doing by subscribing, rating, reviewing, and recommending us. Thanks for listening. Until next time.