Podcast #25: Aligning Data to Business Value

Good day, this is Ed Maguire, Insights Partner at Momenta Partners, with another episode of our Momenta Edge podcast, and today we have a special guest Dan Yarmoluk who is Director of IoT for AETK Technologies. Dan and I have been in conversation for quite a while about IoT, Connected Industry, advanced technologies; Dan’s a super-thoughtful writer and blogger, he’s got a podcast on Verta.ai which I recommend checking out, and we’re going to dive in and discuss some topics that are of mutual interest to us, and our listeners. So, Dan its great to talk to you, and thanks for doing this. 

I can’t believe it’s been probably over a year, maybe a year and a half since we met each other on social media, started swapping stories and conversations, again, ubiquitous communication, it’s cool. 

It is amazing because you find all these smart people in cyberspace! I think what will be super-helpful Dan, and you and I have talked a bit about this, but would love to get a bit of background; what has shaped your view of IoT, and just share a little bit of your experience and what’s brought you to be interested in Connected Industry? 

If you go back philosophically, originally born in Canada, to a Cuban father and American mother, and then at aged 12 I moved to the United States. After that I studied abroad for a number of years, worked and lived in Europe, and later in Asia, so I have a very global view as a foundational thing in my journey. But then in recent years I settled in Minneapolis and I’m around a Midwest view of the world, but it’s like the Missouri ‘Show-me’ state, they want proof points, and value. Also, here is a very hardware-centric community of Medtronic medical devices in Minneapolis, as well as Honeywell and connected people, so there is a very smart Midwest engineering community. That has shaped my background. 

One other thing, about 10-years ago I started selling components, specifically lithium batteries when that was taking off with mobile devices. So, when I was designing in lithium batteries I was around other sensors, it was the first connected product before I really knew what it was, like a telematics product, or a tracking device on an ATM machine, or a FORE was an app they had, a golf GPS for golfers, and I was designing those, since I was starting to get around the idea of how many hundreds of thousands of devices could be connected through those lithium battery cells. So, both location, industry, and perspective are what shapes my view. 

That’s great. So, you’ve got a background in technology, and implementation, it’s an interesting perspective that there are real geographic differences in the IoT or Connected Industry communities, and it’s clear what’s going on in Germany or Bavaria is very different to what’s happening in Asia. Can you talk a bit about that? What is the unique perspective that informs the way you look at the industry, and how the environment where you’re working is shaping that? 

There’s two aspect here, when you’re in the Midwest you know ATEC has an industrial condition moderator in place, so you could think of it as a small scrappy start-up, but funded or capitalized by manufacture, you guys that have been doing it for decades. So, here the industrial IoT buyers like mining, pulp and paper, power, oil and gas, it’s all process. If you can imagine in the Midwest, obviously manufacturing is conservative by nature, and then the Midwest is conservative by nature, so there’s no easy adopters, not early adopters, and you’d have to provide value. So, you have to think about the whole value chain from product or analytics, all the way through, and be very empathetic with the customer journey. 

But along my way I was like this integrator guy, an MBA-type of sales, or strategic sales person, and I just fused it in the last few years with a data science masters, not to really code but to understand how we can leverage this technology, and these business models. So, I suffered in the crowd and the mathematics going back to do that masters at 40 years old, but it served me well to give me a view of what is possible and trying to connect the balance. 

It would be great to get a sense of some of the challenges, projects that you have worked on, and as you watch the industry evolve over the past decade or so. What are some of the changes that have been apparent to you in how businesses look at connected industry, and some of the enabling factors that are necessary to get to outcomes? 

Well, I think what’s really going to be an enabling factor, or what’s happening is really network, in the plants specifically in industrial IoT, so this CAT-3M network play could be very interesting, and if we think down the value chain a little bit more, and I know this is an interesting point for you as Edge Computing, so being able to use some hardware, if it’s an Intelship or whatever that can do this kind of machine learning, or AI, and pump up a segment of that data and send all of it to the Cloud. If we can get this information flowing with network, with Edge Computing, then we can see some real power on the data.  

So, there’s a few things that I think is really shaping, but my sense Ed is, when I’m looking around, clearly how Amazon and Google, and some of these people are allowing and opening up the cloud system and enabling the community, I see some things accelerating under the radar that as Peter Diamandis and all these great guys are talking about, exponential technologies, and all of them converging at the same time, but they’re coming now and I’m excited to see how we shift it to the B2B sphere, the industrial sphere, and just new services, access of service emerging from it. 

Yes, it’s interesting because as people had initially thought about IoT, that was very much a consumer-driven concept, a focus on home automation, connected appliances and that sort of thing. But clearly, we’ve had a meaningful focus on key industries. In you view what have been some of the most important driving technological forces? You and I are both fans of the work that SingularityU is doing around exponentials, but I’d love to get your take on what you see as those key forces that people need to be paying attention to? 

I think it’s the unconventional wisdom that you and I like to uncover. I think there’s a lot of enabling technologies that provide a very interesting type of patterns of information that could let us go to these new worlds of business models. The ecosystem in my mind hasn’t sunk up together, we have these data-science solutions that are talking about models, but they don’t really understand the subject matter expertise, at which they’re applying these models. So, we’ve really got to get this triable knowledge of experts to help fuse this, as we hear all the time, IT and OT together, to have a greater friction to deliver a model. But, to be honest Ed, I don’t know what your opinion is, but for this last six-months I’ve just seen a tsunami of machine learning in AI companies come out saying, they’re offering the same type of agile or agnostic analytic solution on top of any industry. I think we’re getting to a point where we’re focusing on the shiny object of precise prediction, versus radical or obsession with the customer journey.  

I just think the market will have to mature, there’s going to be this period of business models that solve problems today, and before we get to a totally connective or automated world. So, we have a decade to bridge the gap, and I don’t see too many people talking about that evolutionary road of an aging industrial maintenance worker enabling this tech, and he’s going to retire soon; then we have a new generation coming in, and what is going to be the way that this is rolled out so we can get an ROI on all the investments these guys have been making? 

So, I don’t think people are connecting the dots because the financial incentives with these huge companies, the big ones that you know has relied on a dealer network which means they’re away from the customer, which means they don’t really understand the pain, or are really sympathetic to the customer journey enough to make it radically simple, and put it in the background. So, I don’t know if I’m getting old and grumpy, or I’m maturing, or its almost going from primitive to complex, as Ralph said in your previous podcast, ‘actually simple’, and I do agree with that statement. 

It’s really interesting because I’ve just had a conversation with Rob Tiffany, and one of the points he was making is that it does come back to this bright shiny object argument, that vendors get enamored with new technologies, and certainly companies do, they want to be able to say that they can check-off all the latest buzzwords. But the point he was making, the subtext very much ties into the point you’re making is that fundamental business value is out there, it’s ready to be captured, and in many respects, it’s being overlooked by an obsession with having your feet in a pool of the most advanced technologies, even before they deliver value.  

That’s exactly right, and I’m just stuck, or for lack of a better word, in the Midwest having interface with these people so it’s a very apparent ‘in my face’. I don’t know if my view would be honed or I would look at it differently from a different part of the country, because its tech talk, and product development, and product release, and then scale. But here it’s like I’m having to fight and think of value delivered, it makes us think harder and more innovatively, but you wonder who’s going to emerge victorious out of this whole game, the big-big players. I just like you am fascinated by it; how do we connect this community together? But I will tell you that I am more encouraged this year than I was last year, so I believe it’s improving. 

In your experience, how have the conversations changed, when you’re dealing with skeptical, conservative companies who have built resilient businesses that have been around for a long time, and you’re pretty much where the rubber hits the road; how would you say the conversation within companies has changed as it relates to connected assets, newer technologies, but also the broader theme of digital transformation, which seems to be becoming the catch-all? 

Well I think a lot of people just want to pick my brain on these things in a variety of either analytic solutions, or eco-system partners, or interested friends and acquaintances, like yourself. I think people are now accepting it, and are now getting into the driveboard, and what does a good PLC beyond the early adopters that just spent lots of money, and have mixed results, and we don’t even know what results we’re expecting. Yes, we say cost, yes, we say more efficiency, but how its applied at that one specific point I think is sometimes lost. So, I do think it’s like its accepted, now it’s like let’s get down to the drawing board and really design out some used cases, or some measures of success, which is tough. 

This is a broad question, but how would you assess the capabilities of established businesses? We’re talking about industrial businesses, in being able to effectively chart out a digitization strategy, a strategy to connect their businesses with potentially new business models, and technologies, do they have the capabilities? 

I think a lot of them don’t. It’s just been the evolution of their companies, and they don’t have that digital DNA per se present, because it wasn’t needed in that. Manufacturing again, as I was saying, is conservative in nature, don’t deviate from the norm because you’re trying to get through putting efficiencies and processes in. Now we’re coming in with all these different inventive ways to take data out, to play with it, to potentially erupt, say things that are different, and they’re just not equipped to consume the kind of technology that we’re throwing at them. Or, it might not be quite as valuable as we thought it was. So, we’re in education phase of saying, ‘Hey, you have to think of having a hybrid  IT-OT rolled that is different from what you had yesteryear’ and are starting to think like that. Some of them are solving specific pain points, and trying to connect that one difficult asset up, and start having data that was around that pain point. Now, that one connected asset is not economical for a big technology company to get the ROI that they want, but you have to understand that that’s a proof point for these guys to move forward, so there’s little experiments going on, is the short way of putting it. 

There’s been a lot of focus on predictive maintenance, or even prescriptive maintenance, but certainly one of the points that you made, and keeps coming up is that a lot of machines or operations in businesses that have depended on sometimes multi-decade capital replacement cycles, just have difficulty getting basic data about what’s going on. Are you seeing any change in movement in terms of the instrumentation of some legacy machines, for instance? 

Well, all I deal with is legacy machines. This is a great question, 70 percent of all industrial equipment is like World War II age; it’s like, so my colleague and I were stuck at the airport last night, it’s like a 1940’s car, when I go in there as a guy who used to run reliability engineering for a big company, it’s a 1940’s car, was it out in the garage or was it stored out and treated like junk? Then we have to try to connect this asset and start having a theory, and you have to think more Ed, it’s not just like, here you connect it, there’s vibration data, with that data you’ll see patterns. You’ll never solve their problem, ‘This is what this data is, this is what we think it will yield, and tell me what you notice’, and then we have to connect those dots. So, it’s very slow, it’s a game of inches and you’re trying to push these. 

Eventually, people are talking about this information or resolution-revolution as they call it, the granularity of the data actually lines up with their tribal thinking, it can be predictive. But the other issue is, people are putting on sensors that don’t have the granularity necessary to give them any predictive analytics, they’re putting in energy bands or sensors that they can’t get the resolution required to give them any kind of 36-90-day predictive thing to make an adjustment. A big factory as I understand, it can’t just shut down, they need to schedule it in, and if the sensor data is not giving enough attunity to be able to sense thing, and nothing to advance, but they’re cheap. So, they’re like 30-bucks, or they’ll do it on a SAS model, but the reality is it’s not giving them… 

So, we’re starting to see this group of people who did PLCs come out and say, ‘I did it with those cheap ones, and it was a failure’. So, we’re learning from some of these failures hopefully, and then moving onto a … because they don’t know the right business model or the investment, we don’t know how much they are going to pay for this, what is value? If an industrial company is going to change all their strategies based upon a connected strategy, they have to have some barometers as to what success is, or how much to invest. We’re not giving them quite the right answer I think, it’s a little scary for these guys. 

You touched on a really interesting point that I hadn’t heard before, and one of the themes of conversations that we’ve been having over the last couple of years is, why the IoT boom that I think a lot of people predicted in say 2013-2014, why that really didn’t materialize to the extent that some of the more aggressive expectations had anticipated, then you get stuck in this proof of concept loop. I think you just hit on a really interesting point with the idea that the sensors were lacking, that you weren’t getting the right data from the sensors. I think in the sense when you just want to connect something that’s cheap you get data from it, that if you’re not thoughtful about the granularity, or essentially how the accuracy, or the scope of what you’re measuring… and it seems like it’s taken a while to figure out.  

Do you think that some of these initial experiences have resulted in lessons learned, that will make the next round a proof of concepts be better informed, and have better chances of success?  

Well that’s a thing, I hope so. I take it is, because we’ve had some of those failures. The thing is, nobody has all this knowledge, we’re leveraging those sensors because they came out of the iPhone and they have been cheap, so we’re using them saying we had vibration. There is a whole world of vibration analysts that took five levels of certification of wave forms, and 100,000 data points per second. So, there is a domain of expertise that no one is leveraging; they are on the side lines, they had very expensive $250,000 diagnostic tools, but people are just saying, ‘I’ve got a little sensor here between zero and 1,000 Hz, and then that guy’s got zero to 30,000 Hz to measure energy bands of rotating equipment such as ball-bearings, then you can tell if a certain sound is indicating a problem. 

So, I just don’t know why the technology groups haven’t really embraced those domains. They have those two groups who I haven’t really met, there’s a few groups who are trying to facilitate that communication. One you might know about is called Reliability Web, they just did the IBM Maximo Conference, that’s where I was at in Orlando, Florida. So, its Maximo as an IBM product, that is a computerized maintenance management service, so it’s like a work order system that sits on top of SAP, and its ubiquitous across many-many manufacturing organizations. So, we need to take our sensor data and automate it to the worker. We’re trying to connect the dots to go, ‘Hey, we’re not gonna just let them look at descriptive analytics, we’re going to integrate it all the way to…you’re not telling them what to do with that problem asset’. 

It’s just this mass of chain of connecting the dots all the way down to the end. You have to have a passion for this stuff because it’s not easy. 

And it seems it is such a broad-based or far-reached problem with such extensive scope, that the only way that you can really accomplish true connected vision is by taking each step of the chain, one by one. 

Yes, and I don’t think people are talking to those kinds of people. I think they’re talking to each other, so it’s kind of a vacuum out there. It’s like vendors talking to vendors, and I’m like, ‘Why aren’t we talking to the people that matter, if we want to accelerate it, we need to understand’. So, this gets to the point again of who is touching the customer, and who understands their pain? Those are usually these integrator-type of organizations that are on the frontlines, goal partners that are interfacing between both that enabling technology, as well as certain vertical solutions, which have always been servicing, like industrial networking groups, and they maintain those servers for decades, and then they can understand how to place sensors, or what their problems are. 

So, its truly eco-system playing, when we hear that time and time again. I couldn’t think of it any other way. 

It truly is, when you talk about the need for interoperability and cooperation across so many different stakeholders, yes, the challenges of bringing some of these… I like your analogy there of these World War II era automobiles into the contemporary technology of preparing for the future. It requires a lot of different inputs and involvement. 

I’d like to turn the focus to analytics, AI, and machine learning. I think your experience has got to be really helpful in getting that immersion in data-science. How have you seen the evolution of some of the technologies, for one, that we’ve had all the open-sourced tools, the declining cost of some of the storage options, obviously there are some very powerful databases and tools, but how do you see this proliferation of tools being able to be applied with I’d say appropriate value-add, and appropriate contextual impact, to really ensure that the industry, and certainly the value that the customers see, are able to move forward? 

Well this is an interesting question, because all these tools are available now. I notice that you definitely get into the details Ed, and if you did a little bit of data science like a couple of classes, you would start niggling around, GitHub or Stack Overflow, or these Azure Platforms, or WhatsIn, or AWS and start going, ‘Wow!’ Here’s some tools, and there’s some datasets. Millions of people can start playing around, that is just insane to me, and when you talk about resources, I know we always talk about great books or stuff like that, these massive online courses that have data science for free, from the best guy that does machine learning, Andrew Neg on Coursera, and if you want a certification you can pay 95-bucks, otherwise its free. And then these toolsets are free from AWS, all these places where you can have a SandBox and start playing. Contextually you have to add it, this is the great question of the day, and I think there’s these vertical specialized companies, you see them in oil and gas, these analytic companies that are going to solve a problem or two, and they will be scooped up by a big company. 

I get the feeling people solving those problems, leveraging some of those technologies are going to win in the long term, because they just know context. But people that have no real sense of data-science even though they’re doing types of data science, what they call relational databases, and they call it prediction or rules based, but a couple of more steps and they’re doing machine learning, but they don’t even know they are. So, I just see a lot of cool people from all sides of the globe being able to develop solutions and contacts that… and I don’t know about you, but I feel there’s a bunch of stuff going on around China, beyond what we read about SoftBank, beneath the surface, that’s probably incredibly interesting, that we just haven’t been able to assess yet. 

That touches on an interesting point which is, the idea that you have billions of minds that are coming online, getting connected and empowered with these tools that frankly are getting easier, and easier to use, is really unlocking some incredible potential, a lot of it we really haven’t imagined yet. But what happens as well is, you start to get the acceleration of innovation, which again starts to outpace the capture of value, or the ability to generate value in say blockchain, there’s a perfect example. We’d love to get a sense of what conversations you may be hearing around blockchain. I’m here in New York, this is Ground Zero for finance, we’ve had this cryptomania, and a lot of folks in FinTech, see crypto through the lens of just another asset to trade, another way to automate back office processes. 

Just today there was an announcement by IBM and Maersk that they’ve got, I think, 78 companies in their consortium to develop a provenance blockchain, so how are people talking about it, or thinking about blockchain in practical ways? Is anybody playing around, are any of the conservative companies playing around with the technology, in your knowledge? 

Yes, I think IBM and Maersk is a great example because it’s got many participants in that shipping chain, and all that paperwork as you can imagine. Just being out in New York you know people that were in the shipping business, or analyst guys that talk about all that stuff. I am seeing people talk about it, we have this issue where we’re really worried on the one hand about cyber-security, and this appears to be a way to have some kind of security.  

But I think there’s a couple of big holes that we have to fill with blockchain; one is the used case in the computing power to be able to do it, even if it’s a private blockchain… between you and I every time we hear something there’s a blockchain being hacked. So, somehow the public perception has to get over the fact we say its decentralized, you can’t hack a million computers and then there’s a guy hacking the computer and taking the money. I don’t know, that just gives me a little bit of pause, even though I’m doing blockchain developer classes right now on IBM, and I’m very interested, so I’m not down on it but if we’re going to use it we’ve got to make sure some of this stuff is bait. 

No doubt the security issue is pretty unbelievable, not so much about the trustworthiness of the technology when you’re writing information to a blockchain, but it certainly is a space where you see the extremes, both the best and worst of human nature. 

Yes, it’s crazy. I’m keeping up with it, but I have a friend that has a legal tech company, he has a patent technology, he’s a patent lawyer – one of the biggest patent lawyers in the country, and he developed certain legal tech things to help with automated processes and returns. Then now it spun out as a legal tech company outside of his firm. People are thinking of a blockchain for looking at patent renewals, so it would be verified and trusted that that patent under a huge corporate patent portfolio when people are searching for these things is verified on blockchain. So, this is where Ed, you and I would probably have never thought it out, then you hear it and you’re like, ‘Wow! That’s a great use case’, but it was born out of industry, not out of a tech company. This is born out of a tech-savvy, growing, large legal office. You can imagine that? 

Yes, it is really remarkable. There are so many industries just being rethought, reimagined right now with this idea of a distributed trust layer, but I think the practical applications in industry, we are super-early-on. I’d love to get a sense of your view since you got the conversations with folks in manufacturing, are there any technology hurdles or enablers that you think maybe are under-appreciated, or conversely over-hyped, that people should either pay more attention to, or ignore? 

On both sides of the fence I would call this both hurdle or an enabler, depending on how you look at it, which is people, process, business case, user experience, and in the manufacturing world to me that means integration into their workflow. So, those are both the hurdles and the enablers, and if we can get our thinking and our thought process around they are possible, but they’re skeptical really put an effort through to get it done, I think we’re on for a special ride the next couple of decades. 

Any particular industries that appeal to you, or that you would regard as forward-thinking, or doing things the right way? 

Well, I think its born out of necessity now, the stuff I’m reading about the auto industry is really incredible; we have robotics, we have AI, we have electric, we have the mobile entertainment system in the connected car, and the driverless car, all happening at the same time, and a changing millennial bio group that look at the TV differently, or the mobile entertainment system as the main component to buy as opposed to the engine! Talk about connecting the dots, I think they’re connecting the dots, and the stuff I read is fascinating. Still, just mobility in general, and social, communication, and connecting to people, I think there’s still an amazing concept in this what’s coming up around the world, and being able to communicate, just tells me solutions are going to come from all over the place Ed. 

We often think of these big American companies that we have, we have this huge company that has prowess, money, and is a gigantic software company now, which is Siemens. We have Asia and China, we know make SoftBank billion-dollar investment in data, but I don’t think we’re really feeling how deep that goes. You and I read it, we know it. Did you see those numbers about Ali Baba with regards to his Ant, online lending with…? 

Yes, Ant Financial, the scope of what’s happening in China is mind-boggling how big these businesses are scaling. 

Didn’t that just happen like very radically, we almost shipped the entire financial? I ask you because you have that analyst background in that line, where I think I’m just reading it shook up the whole industry. But I think that was totally unintentional, he was trying to enable part his supply chain, or his people, his customers to be able to buy stuff, then suddenly… I just see a lot of things mutating that we never thought of before, from this hypoconnectivity. 

Well that’s an interesting point too, and some of the conversations that I’ve had over the years have really brought that out. One conversation about supply chain, ultimately this was Disney putting sensors on all their seafood because they wanted to reduce spoilage, and essentially avoid any liability of serving tainted seafood that would make their customers sick, through the restaurants down in Disneyworld. It turns out that ended up having enormous financial benefits and efficiency, they drove efficiency gains from a solution that was designed for one purpose, yet the real value serendipitously came out of a whole different aspect. Have you seen that play out on your side? 

Well there is a local here group, just a local company that I know of, that I’ve talked with, it’s a company called Restaurant Technologies, they had a dumb product that was a vat for cooking oil, then they wanted to do something different. They were the manufacturer of this metal product, they put a sensor on it, it was for the cooking oil for McDonalds. It sensed when it needed to be changed, then they did the delivery for a certain section of the country of the frying oil. The frying oil or whatever is the second-highest cost after the protein, so it’s very significant to the bottom-line, and its managed and outsourced so they make this product, and they monitor it, and then they replenish. So, it went from these guys that did a dumb product, to trying to provide more value, and it was born out of industry, I think it was probably borne out of McDonalds and these guys saying, ‘Can you do this?’ and you don’t even want to do this part any more.  

So, like you were saying, I think it was serendipitous, I don’t think it was necessarily planned, but we see these opportunities pop up, these anomalies in the US and we have to be able to go, ‘Hey, that could be a watershed moment for us, to be able to take advantage and look at the things differently’. So, to me that’s the fun, the most interesting part is to watch what pops up out of this. It gives the little guy a chance at the end of the day, it gives a person who might have a good idea and work hard under a hyperconnected environment, to be able to play in this space; whereas in yesteryear it was all distribution, it was all channel domination, and who had money or airwaves. But I think today it’s different. 

That’s an interesting point this idea that you get real democratization of technology, and a way to level the playing-field as it were. It’s interesting that a lot of people in media initially thought that the internet would provide that longtail for businesses, particularly in digital media, music and print, that ultimately everybody would be able to have a platform. Of course, what’s happened, is you’ve ended up with this incredible concentration of these big portals and these giants. Now, the realities of companies that build and sell physical products is very different, and I think the idea of potentially creating experiences from the products, and being able to build subscription revenues, or databased revenues from products and product expertise and really unique knowledge, is something that’s quite different. 

I’d love to get your perspective on where you’re optimistic, and where you might have some concerns for the smaller companies out there. 

Well, I get worried that people are not understanding what’s happening from a macro-economic standpoint. Whether it be the politicians and just taking automation or AI, or just regulating and kind of thinking this is cute kind of Amazon stuff, which is now just a gigantic company, and people making it into an international-type of conversation where its automation, or Asia vs America, I think this is humanity progressing, its global macroeconomics, and I think we’ve got to embrace it because it’s going to happen. I get a little afraid for these people who are not at least in touch with some technology, because they could be displaced, or their children could be displaced. So, I worry about that, I think there’s a little bit of blindness to what’s going on in the general public. It’s labeled as gaming, or Fortnite, Fortnite is a gaming phenomenon, and they think it’s cute, but at the same time that’s captured hundreds of millions of kid’s attention for dozens of hours a night. This is a different world than it used to be. 

It is, people are growing up with very different context. 

An interesting point is when you’re talking about service business models, well my nephew is 23 moved down, going to graduate school here in Minnesota, he’s staying with my family and I, he doesn’t care about ownership, he cares about results and service, the Uber business model. That’s just going to have an effect, in the industrial plant if they are not wanting to deal with data, well the younger generation coming in will want to deal with data. So, it’s going to happen, it’s a question of when and how. 

Of course, thinking about certainly new business models, even the generational changes and how people think about work, and think about the relationships to companies, you create a lot of issues as well. Any thoughts on the talent side, the skillsets that you see are going to be necessary for success in the future? 

Well, I think McKenzie gets this pretty well spot-on what the label as a data translator which is the path that I fell on, which is the person that does have an education in some of these advanced technologies, when it’s not like coding that behind the scene that can communicate business, business needs to get into technical requirements, for want of a better word project manage these things to the goal line, or to fruition. I think software skills and coding skills at some level are really important, there’s just such a gap of these software development engineers, that it is creating a new world of low coded environments. It’s kind of funny, because the lack of coders is driving low or light-coded environments for development, I think super-coders are going to code coders out of business in some of these areas. 

So again, back to your point of all these cool machine learning tools, and all this stuff, well as in the new book from that guy from the University of Toronto, AJ or Ageral, you probably know this guy, if everybody has got high precision or prediction, based upon artificial intelligence and machine learning, then the question becomes what are you going to do with it? Because then if the tool, the precision of your data had better be right, or your business model, or your ease of use had better be good in my mind, if that world or that future comes to pass. So, the more and more I think about it Ed, the more and more I think it’s got to be simple, and has to think of the customer journey more and more, and the tech is in the background. 

That’s a great point, I think you hit on it. Ultimately with the mathematics, with the technology, it all comes back to solving the customer problems, and essentially becoming transparent, they’re invisible to the users, rather than being this domain of high priests, or technical mandarins! 

Exactly, and I think these guys are bubbling up, I think they’re bubbling up and they’re making money, but you don’t hear about them because they’re busy doing stuff, they’re knee-deep in doing stuff. They’re the people that you and I would want to talk to, would want to learn from, but they’re busy, and good for them. 

I think we’ve covered a great number of topics and insights, I really appreciate your thoughts and input. I always like to ask a question of all our guests which is on a book recommendation, if there’s something that you would recommend to our listeners, either a book, or resource? 

I’ve got tons of books, this is how I’ve learnt in the last few years, I just consumed stuff. I’ll give you a few books that I really like as of late, one is by a guy named Travis Wright, called ‘Digital Sense’. 

Travis, he does a podcast with Joel Comm. 

Yes, he does the crypto podcast.  

I see his Facebook feed all the time, so that’s a great recommendation. 

He kind of weaves together marketing customer experience, social media stuff. That might not be everything to an IoT listener-base, but there’s a lot of lessons learned. I really liked ‘The Mathematical Corporation’, by Josh Sullivan and Angela Zutavern, obviously the Peter Diamandis books if you want to go a little heavier in AI ‘Prediction Machines’. 

But as a resource to people that want to look more, those EdX or Coursera courses are really open to people, being free or very cheap. I would encourage people that are of any age; I went back for my second master’s at 40, to go back, because we’re going to live longer, and you’re going to have to work longer with social security, so there’s no rule that says you have to be a lawyer ever since you graduated law school, for the rest of your life. You could participate in this world if you want. 

That’s great input. I do think we are in an era of lifelong learning, and the ability to change is really going to be a key core skillset, those are some great resources. 

Dan, it’s been great talking to you. Again, this is Ed Maguire, Insights Partner at Momenta Partners, and we’ve been speaking with Dan Yarmoluk, Director of IoT, AETK Technologies. Again, thanks everybody for listening, we’ll post the links in the show notes, and Dan thanks once again. 

Thank you very much Ed, I appreciate it.