A Sensor-Enabled World

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Audio transcript:

Episode 2 – A Sensor-Enabled World

Published March 17, 2017

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Announcer: You're listening to Technomics. Connecting you to insights on digital transformation and the marketplace, with your hosts: Robyn Itule and Jeremy Nelson. The hosts' opinions are their own. Enjoy the show!

Curt Cornum: Hello and welcome to Technomics. I’m Curt Cornum and I will be your new guest host. Robyn and Jeremy are still around, but as Insight’s resident chief geek, I have some expertise and a true passion around infrastructure, so they've asked me to help out with the conversations. As some of you may know if you've followed me on LinkedIn that my headline is, I’m on a mission to help people put technology to work. What I mean by that is I can geek out with the best of them at a personal level, but really from a business perspective, I really feel that if you can’t connect the technology from great ideas to meaningful results, then it really doesn't matter. And so that's why it's a passion of mine to help people understand infrastructure and how they can use it to drive their business forward. So a few weeks ago, we held our intelligent technology forum, which is a live stream event. And as the name implies, these events are streamed live over the Internet. And what we like to do with these is to bring together experts around a topic to help people understand what the future holds. At our most recent live stream, we talked about real time business and the Internet of things. You know there’s a lot of hype around Internet of things today. But I think the panelists did a great job of de-mystifying the Internet of things and making it real for people in terms of how they can use that technology to make a difference in their business. We had some great discussions around a real-time business and the Internet of things, and I thought there were some interesting and different perspectives they came up. A couple of our guests you may be familiar with. They've been on podcasts before that we've had. Bob Familiar is our Director of National Practice at BlueMetal. And then we also had Dan Gutwein who's the Director of Retell Analytics at Intel. Like I said, it was a great panel discussion, and I think we're going to highlight some of the topics that we talked about today. We’re going to give you a chance to hear from the expert panels on the real-time business and Internet of things live stream. So here it goes.

Robyn Itule: Welcome to Insight’s Intelligent Technology Forum. Today we are going to be talking about real-time business and Internet of things (IoT). I will be your moderator for today's discussion, my name’s Robyn Itule. So today we are talking about the Internet of things and real-time business. IHS, which is an analyst firm, is projecting that the IoT market is going to reach over thirty billion connected devices by the year 2020; which, just three years out. And over seventy billion in another five years, so that more than doubles. Market leaders are arguing that the Internet of things has been around for decades, but it's really coming into maybe what Kevin Kelly (assumed) calls, reference to Curt and some of our similar reading here, cognifying a number of things. And that's going to be driving factor in the conversation today. Using those data and analytics to help make business decisions, drive innovation, and meet consumer needs is creating more competition than ever. In fact, McKenzie Institute estimates that the total IoT market size is going to reach 3.7 trillion by the year 2020 as well. So there are big numbers attached to this. Not only in terms of devices, but also in terms of market opportunity. So today, to help us have this discussion and discuss what the real opportunity is and how to get there, three of our distinguished guests. We have on the end over here, Mr. Bob Familiar. Bob brings more than 30 years of industry experience with marked expertise in the IoT, cloud, DevOps, consulting and software. He is the Director of National Practice at BlueMetal. Bob is also a published author of microservices, IoT, and Azure. And he also holds a patent in object relational database design; some extremely sophisticated introduction. Welcome, we're so grateful to have you and your expertise this morning.

Bob Familiar: It’s great to be here.

Robyn Itule: Next to Bob, we have Dan Gutwein, Gutwien? I didn’t ask you that before the live stream. This is the beauty of live TV.

Dan Gutwein: Everything works but Gutwein is how its pronounced. But it’s up to you.

Robyn Itule: There you have it, now we have the correct pronunciation. And Dan is the Director of Retail Analytics in the Retail Solutions Division at Intel, and part of the Internet of things group. He has more than 25 years’ experience in helping customers solve business problems with technology solutions; from start-ups to large corporations. Welcome, thanks.

Dan Gutwein: Thank you.

Robyn Itule: Apologies for butchering your name.

Dan Gutwein: No problem at all.

Robyn Itule: And of course, we have Curt Cornum who is our Chief Solution Architect and a Vice President of Services with Insight. Curt helps our clients navigate the changing technology landscape and businesses and IT leaders develop solutions and frameworks and references that put technology to work to deliver meaningful solutions.

Curt Cornum: Good morning Robyn.

Robyn Itule: Good to have you guys. Alright, so let’s dive right in. There's some really, really interesting conversations happening around real-time business and Internet of things. In fact, you could almost argue that there's a bit of a marketplace saturation in terms of the conversation. Which really gives us an imperative to bring some actual clarity to it. It's not just buzz words, there's real meaning behind this. So why are businesses striving to get real-time data from products, environments, consumers, employees, and partners as well? I’ll send that one to you Dan.

Dan Gutwein: Great question by the way. I think I would rephrase it a little bit. It’s not just about having the real-time data, but being able to take real-time actions with the data you receive. I work almost exclusively in retail and our products and solutions obviously go through a lot of industries and verticals and Internet of things group. But retailers aren’t short of data, they’ve got plenty of data. They're short on being able to take actions on that data in a timely fashion. And I think gone are the days when we're looking backwards and trying to figure out what happened last 13 weeks and figure out how to take that in today's environment. Or what happened last Mother’s Day is going to happen this Mother's Day because things change. They’re dynamic, they’re fluid at all times. And the Internet of things is helping make those decisions in your real-time. Real time is a relative term I think, but certainly in near real-time.

Curt Cornum: Yeah, just to add a bit. You mentioned that some of this is not new. That we’ve talked to folks and they’ve been doing Internet of things for some time and that's true, especially in the machine side and what they call the carpeted areas. But two areas that there's a lot of investment in right now: one is around the changing customer expectations. We’re all consumers at one point or another in our lives and we're hyper connected. And that's creating some interesting behaviors. We're more informed than we've ever been, and we’re probably more skeptical than we've ever been, and we’re more socially aware and socially connected and I just think that drives a lot of different behaviors in the way that folks interact with their customers today. So that's one aspect of it. Then when you flip that, and you look at the work force that we have today, the workforce is really changing. We're talking earlier, if you look at Insight, we've got an age range from eighteen to seventy-five the work at Insight. So we have 5 generations that are working for Insight right now. We get people so old, they don't know how to do email, we got people so young they don't know how to do email. Or they refuse to use emails may be more appropriate. And somewhere in there, when you look at the young side, the post millennials, they’re really the true digital natives. They don’t really remember life before an iPhone. They were like 9 or 10 years old, the oldest ones when the iPhone came out. So if you look at the workforce, where it’s going to be in 3 years, it’ll be over 50% millennials and 10% post-millennials. So you have this 60% of the workforce in 2 or 3 that are just going to demand data more real-time. That’s just the direction that they’re going. Staying in the rear-view mirror view just doesn't really appeal to that crowd. There's just been an expectation that’s been set. So there’s those two things and then this whole subscription economy that we may talk about later around how its enabling things, it's more of an enabler. That creates this on demand, what I call this on demand world that we live in today. And that on demand world requires people to figure out real-time business solutions. So to me, that's kind of the crux of what we're seeing and what's different than what we may have seen before where it was infrastructure optimization and trying to get efficiencies out of equipment and things like that. So it’s an interesting time.

Bob Familiar: What I also think is interesting is every business regards of what vertical they’re in, is dealing with this same problem. Over the last several years everyone’s been talking about IoT and there’s been a lot of advancements, and sensors, and single-board computers. They’re all looking to figure out how to leverage this access to data in their business. A lot of companies have been experimenting but it’s interesting to see now the shift to where these solutions are. They’re being rolled out, they’re being operationalized and through the work that we done at BlueMetal, we’re seeing this maturity, in this space where businesses are now seeing the value of getting access to real-time data.

Curt Cornum: So I think the real short answer is about, there's increased competition. So whether you’re competing for in the marketplace or whether you’re competing to hire and retain top talent within your organization, you need be focused on these types technologies and how you can use them to attract both those.

Dan Gutwein: It’s so amazing, Insight thinks you're eighteen years old

[Multiple conversations]

Robyn Itule: So with the increased competition, organization's naturally have to look towards developing more efficiencies and finding new revenue streams. How do real time data and IoT support those initiatives?

Curt Cornum: I know you guys have some great use cases. So I’ll probably defer to Bob and Dan.

Bob Familiar: Yeah what I think is interesting is when companies go get into this space. Clearly there's a technology component to it, so they have to figure out if they manufacturer a product, how are we going to sensor enable this product? How are we going to ingest that information into typically a cloud platform, do some advanced analytics, and build some applications on top of that to be able to take action as Dan was saying. The other side of it though is they have to think about their business model. So what's going to change about our business as a result. It’s interesting to start to see manufacturing companies that are oriented around let’s say a hardware product. They’re going to go to bed as a hardware product and wake up as a software company as a result of this, and that's almost a direct quote from the CEO of GE. So let me give him a little credit for that. But the point is these companies are going through this transformation, so they're going to change. And that can be very challenging culturally. So it's interesting to see the impact of this on the cultures of companies on the skill sets that they need to have, that they have to hire for, or retrain for as they evolve from being oriented around a product to now offering software as a service. And those software applications providing access to this data through rich visualizations and alerts and notifications and things of that sort.

Robyn Itule: Dan, you indicated responsiveness as being a business imperative that real-time data and IoT are starting to enable. It's becoming part of, dare I say it, table stakes for the way that really innovative companies or companies facing a lot of competition are moving. Do you have some examples of ways that organizations have leveraged their real-time data to become responsive?

Dan Gutwein: Yeah, I’ve got several examples. Where to start. One of the case studies that we've gone public with is with Levi Strauss and Company. I think everyone’s familiar with them, an iconic brand, a wonderful company. Several stores around the world; so global distribution, global manufacturing. And we did some studies early on with a couple of research firms and we found out that this inventory issue in the store, understanding where your inventory is. Having the right stock in the right place at the right time equates to, in the retail industry, greater than a one trillion-dollar problem. So we’re not talking about small numbers, we’re talking about massive impact and industry just having overstocks and out of stocks. And so everyone here, everyone listening has gone into some retail store at some particular time and said, “Hey I’m looking for this particular item.” And the associate says, “Well let me try to find it, it says I have one here. I can’t locate it.” That happens all the time. As a matter of fact, independent [inaudible] study that said the on shelf availability of items and retail is around 60-65% in an average retailer. So we worked with Levi Strauss and Company and came out with the retail sensor platform to help their store respond real-time. And it was all about the consumer, taking care of the customer from when they walk in the door and having the right products in the right place at the right time. Making sure that you have all the right sizes out at the right place. Making sure that shopping for a pair of 501s you’re normally not hunting like a 514 section. You’re looking at the 501 section. So making sure things are there. We’re working with Levi Strauss and Company and the retail sensor platform that Intel developed. We’re tracking every single item in every single store within seconds. And we can tell if you take a pair of 501s and throw them in the 514 section on the stores we’ve enabled it. It will alert the associate to go put that back. And so, gone are the days where you’re like let’s go try and get our store organized at the end of the day, at the end of the shift. Its organized now, right now, at the individual given time. So the insights in that are, as you can imagine, are incredible. In retail there’s just the onslaught of pure dotcom plays because they have that data. They know where the data is in their warehouse. They know when it’s going to arrive at your house before you ever click pay. It’s not so much about, are we competing with them, but it’s about when a consumer walks into your store, converting them into a sale. If you don’t have what they want or you can't find it, you’re not converting into a sale. So it’s about satisfying that customer, making sure things are in the right place at the right time. I can give you another quick example that’s interesting too.

Robyn Itule: We’d love to hear it.

Dan Gutwein: I’m sure you would. I hope you do anyway.

Curt Cornum: Nah, keep going.

Dan Gutwein: This is probably near and dear a lot of folks that are actually listening as well, a couple years ago we actually started tagging beer kegs. So if you look at the amount of waste in draft beer, it’s in the billions. There’s a couple hundred million beer kegs at any given time floating around the US alone. And no one knows really where they are. They’re probably in a lot of college campuses or floating in rivers or end tables in people’s houses. But the real challenge is at the bar, if anyone’s ever worked in the food and beverage industry, you know the way to actually tell if there’s enough beer in there is to shake it or kick it. And so we actually have sensors on them now working with a small company up in Indiana called Steady Serve. And we’re able to actually tell that bar owner down to the pint how many pints are left in that keg. So you know when to change it. So you know if you have enough when your busy shift is coming. And that’s interesting and it provides amazing value to those individual bars by just connecting beer kegs. But what’s really interesting is the data that you get back up through the supply chain. As so as you can start looking at consumption levels and pairings and what they do, the end objective is to someday do some perspective predicted analytics that allow us to actually go out and figure out what kind of hops you actually need to plant that you can actually harvest in a couple of years because you understand that demand. And you’re not left out in the cold looking where the consumer demand is going. And again, going back to the same thing, you are fulfilling that consumer demand and satisfying the customer.

Robyn Itule: I’m going to go out on a limb and say that based on these two examples with jeans and fashion and also beer, that this is probably going to be among our highest rated live-streams. So thank you, thank you for that content contribution.

Curt Cornum: Let me tell you a quick story because Dan, I was out at Intel's developer forum a few months ago and Dan was nice enough actually to invite me to go tour the Levi's store. So it's their flagship in the Embarcadero. And so I’m waiting there and Dan shows up and goes Curt, I sure hope those are Levi’s jeans you’re wearing. As it turned out they were my favorite Wrangler jeans. So it kind of started the tour off on a bad note. I’m wearing Wrangler jeans.

Dan Gutwein: You would think we’re Levi’s, you would wear Levi’s.

Curt Cornum: I just wasn’t thinking. So I wore my Wrangler jeans in, we start the demo. They’re showing us Intel’s retail sensor platform and the stylist, she didn’t call me out like Dan did on the Jeans. So she’s got the app there, she’s demoing it. So I’m trying to save face and I’m like, “Hey do you have a pair of dark blue, non-skinny, boot cut jeans in 34/32?” And she goes, “Well let me check.” And she has the app right there and she goes, “You know, we don’t have any here in the store, but it shows we have a pair back in the store room and that’s the next stop on the tour.” And I’m going, “Great.” So a few minutes later, we go back into the stock room and we kind of funnel in there and it looked like the warehouse scene from Raiders of the Lost Ark, if anybody remembers that scene. It was just like this cavernous thing with jeans up to the rafters. And I’m like, “There’s no way in heck she’s going to find these jeans. It’s just not going to happen.” And she disappears, she goes “Let me go get your jeans.” She disappears around the corner, comes back like 10 seconds later and goes, “Got them!” And I’m like, “Are you kidding me?” And so a few minutes and $85 later I now have my new favorite pair of Levi's jeans and I got to tell the story about that and see the retail sensor platform in action which was pretty cool.

Robyn Itule: Your contribution to resolving that multi-trillion-dollar problem.

Curt Cornum: Exactly. I’m doing my part to do that. But it was interesting to see that app live and so I appreciate the invite to go see that because it’s one thing to talk about it, but it’s another thing to experience it. And that’s that whole expectation. Once she said she had them, I didn’t want to leave without them.

Robyn Itule: Well your experience and the platforms and technologies of the new IT that are driving this are two pretty separate things. The ideal being that you really don't have to experience any of that background searching, location, warehousing, all of that. But there's a number of technologies that have to be implemented to make that happen. So can we talk about some of the base layers of this that are required to successfully implement?

Curt Cornum: So this is where the conversation starts to get a little technical but it's pretty fascinating. We've got to take a quick break, but when we come back you'll hear Bob Familiar explain the base layers or what I call the IoT stack that’s needed to build a successful IoT solution.

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Curt Cornum: So thanks for staying with us. Just a moment ago you heard Robyn, our moderator of the livestream, ask our panelists discuss the layers the technology, what I referred to as the IoT stack that must be implemented to make some of these real-time business initiatives happen. Let's take you right back to our conversation. Here's Bob Familiar.

Bob Familiar: I think what's great about those examples is that there are some very consistent patterns that you see there. The ability first of the remote monitor. From that, being able to build up a real-time inventory. If you combine that for example, we did as similar thing with an IoT-enabled vaccine-dispensing refrigerator. So we could track not only the mechanical information about the refrigerator and do what's called predictive maintenance for that to figure out when it would need maintenance and be able to roll a technician and have that operational efficiency as a result. We could also track all the inventory information which now allowed that business to proactively provide a service for replenishment of those vaccines, which can be very expensive. So you want to make sure you never run out of the Malaria vaccine because if you did, now you have a problem in a developing country as an example. So in order to create a solution like that, first it’s the act of adding these low cost sensors and these single board computers. Possibly cellular capability for areas where maybe that don't have rich networking capability. The ability to get these sensors in there, collect the right information, connect it connected to cloud, securely go from the device to the cloud. And these cloud platforms are providing some very rich finish services for doing that. So some kind of a cloud gateway where devices can connect securely, they can send the telemetry, but you can also send commands down to the devices well for doing things like firmware or upgrades. Being able to then bring that information in and in real time do some analytics, do what’s called stream processing. Analyze each of the messages and say if this is just standard telemetry, we’re going to route it over here to telemetry store so that we can make sure that shows up on a dashboard. But to be able to, in real-time, to identify alert or alarm conditions and then route that properly to a service which can do a real-time notification either an email or a text message or different ways that you could inform people in real-time. So you need that capability. Lots of different storage capability in the cloud. You want to take advantage of. There could be some low cost blobs storage for archives There could be a data lake for doing advanced analytics, your hadook-based [assumed] distributed queries or a predictive analytics engine sitting on top of that data store. Certainly relational database, no sequel database and you get all those different types of storage capabilities. You're likely going to build out a set of APIs so that you have a consistent way for applications to access your IoT services and your analytics services. So you have these managed APIs and you have all the different types of ways you can build an application today. It could be a mobile application, a web-based application. And interestingly enough, in an area that folks don’t try to focus on all that much, in the initial implementation of these IoT solutions, the integration to the existing environment. So being able to do, let’s say store forward messaging or a batch based file movement of this information to an on-premise environment for integration your ERP-systems [assumed] and another back end store. So lots of different moving parts. And in order to support all of that as an organization, you need to develop what I would just call your Dev Ops chops. You need to be able to have an organization that can do this continues delivery type of software development life cycle. To be able to rollout constant changes to the cloud. To be able to manage the health of that cloud environment. To automate your software development life cycle end to end. But that also then brings up the fact of now you have all those devices out there. And this is a whole new world of now, “Hey I have to manage tens of thousands, millions of devices.” So one of the applications you typically build is this operational knock. It’s this ability to get visibility into all interconnected devices, know what their health status is, be able to select subsets and perform firmware upgrades, be able to do what's called command and control down to those devices. And of course receive all telemetry for all the rich data visualization. So again, when you get into this, there’s lots of different types of technologies you have to deal with. You have to handle the security across all of that. And you have to have the ability to manage those applications using automation which in the industry today, we call that Dev Ops.

Robyn Itule: So it’s an enormous undertaking that also sounds like it really requires some thinking around your business model.

Curt Cornum: Sure.

Robyn Itule: So what kind of things are businesses considering as they're making that move to real-time and IoT?

Curt Cornum: Dan, do you want to take this?

Dan Gutwein: Yeah, I’m also going to comment a little bit on what you said as well. You said there are a lot of moving parts and items. There are. We talked a little bit about the Levi’s stuff and the beer kegs and there’s so many more examples we could go into. And I think one important note to make is that we built a really incredible platform, but this stuff isn’t super easy yet, I’m being honest. And that’s why you’ve got to work with someone that can install it, service it, manage it, write the application code as well. Because as much as we want to just plug these things in and have them start doing things, it’s not that easy. There’s a lot of challenges and as I keep reminding people, these aren’t problems we just uncovered. We’ve had these problems since the beginning of time. But anyway, just a caveat on that. You asked about the business process and the business changes, one of the biggest issues with IoT, I mean if you think about even apparel. They’re now projecting by 2020 tagging like 25 billion items. How do you do that? Where do you do that? If there’s error when you actually program the item, there’s going to be error in your results. We have a lot of folks that want to try and do it on their own, for some cost issues, whatever the case is. There are challenges and it will be, we think we’re getting pretty close to getting all those challenges ironed out. But there’s not one company that I know of that can bring the entire end to end solution. You’ve got to have folks that know what they’re doing and the individual things. I’ll give you a prime example. We’re working with a large hospital chain about how do you take the data from sensing patients going in, not the individual, but the patients going through this process, and help them get through the process faster. So your wristband can be sensed. And if there’s no logic though, and you have to go into x-ray or you have to go and get your bloodwork done, x-ray is busy, there’s not logic to say, oh go reroute them here and bring them back here. And so you kind of just sit in the queue which everyone enjoys and loves right? No. So when we started sensing them, all of a sudden, we realized that when a patient was laying flat, we couldn’t read the data. Because the water in your bodies canceled out the signal. So we were like “oh, something we didn’t think know. There are interferences with the signal, and there’s a lot of detail that would bore people. Again, a little bit of patience too from all the verticals in the industry. We’re solving problems that have been around for hundreds and hundreds of years and its really exciting. But it’s also challenging.

Curt Cornum: Just a couple points on the technology, because Bob I think you did a great job on the effects of what I call the IoT stack, which is everything from the things all the way up through the analytics and eventually some kind of endpoints that you’re using to do some kind of visualization or actually getting the data and trying get some insight out of that. So that’s a big part of it. And there’s a couple of enablers there. We mentioned the sensors, the storage, all of those things have come down in price, so they’ve made it much more available. So we’re seeing people create, make things smart that we would all probably argue shouldn’t be smart quite honestly. And just having them connect doesn’t make them smart is another piece of it. And I think another one of the enablers there besides the cost piece that’s come out on those components is those standards piece and those standards that are out there today doing a lot to promote the industry. So when you look at things like Bluetooth low energy and wi-fi and Zigbee from a connectivity standpoint, the assumption that that connectivity is available makes it much easier for somebody to develop a product today because there’s an assumption that that’s available. It’s still not easy. And then I mentioned a bit about the subscription economy. So when you look these IoT platforms that are really starting to mature and create, they’re really starting to take on much more of that IoT stack. Today everything from device, command and control, some of the streaming analytics, to all of the APIs to tie all of this together. They’re getting so much more powerful, it’s really making it easier to develop and wire these solutions together than it used to be. But at the same time you talked about business models changing. People have this expectation I believe in this on-demand world that we live in today where it’s not so much, “I want to buy your product.” Its “I want to pay you for the value I get from your product. So when you start delivering these products out to the marketplace, the expectations are changing around, I don’t really want the product, I just want to pay for the value of that product. And if you’re a product manufacture which we've seen is now that you provide a product that can be connected, there's an expectation that you can provide some kind of insight that you can actually see that product where you never had to have that. You never had that expectation on you as a manufacturer before. So it's changing those business models and there's some disruption around what we have to have people trying to do within our own organization and we’re seeing it with end-users. I know Bob and I talked to a client that’s in property management. And they’re looking at doing smart locks and smart thermostats and smart lighting. So they’ve never done that as an IT staff, they’ve never dealt with the things before. They’ve dealt with desktops and laptops and printers and those types of things. So now they have to deal with the scaling of these thousands of devices and there’s a scaling issue and there’s a diversity issue of those devices and how do they integrate that into their IT functions. So it’s really disrupting the IT functions there and they really need to retool their labor force to be able to take advantage of that.

Robyn Itule: Conversely speaking, it's no longer about the things, it is about the experience. And that's what's forcing the transition in the business model. So where Levi's is a great example, well-recognized quality product, now they’re moving towards more experiential approach to their product.

Curt Cornum: Yeah its really never, well I shouldn’t say it’s never been about the thing. The real star of the show is the data. It’s the insight that you get from any of these things that you’re connecting. So just connecting them isn’t enough. We were talking offline, CES was last weekend. There was just a ton of “smart products” that were just being demoed there. From walking sticks to shoes to a monitor so it would tell you when your shower temp was just right. I’ve always done a pretty good job just reaching in and feeling the water. I don’t think I need a solution for that one. And then another one was a hairbrush and it’s a “smart hairbrush” that has a sensor in it. There’s no LEDs in it, but you brush your hair and tries to sense, are you brushing enough times. But also, what’s the quality of your hair. So it’s trying to sense things about your hair and then they’ve partnered with some hair care products and then you have a mobile app and it gives you recommendations on, you need a shampoo and conditioner that’s going to strengthen your hair or its dry, or its damaged or its whatever.

Bob Familiar: It’s called IoT gone bad.

Curt Cornum: I won’t go too into detail. I did write an article on LinkedIn, it was called IoT, when smart things get creepy. And I went in kind of deep around that subject. But its real.

Dan Gutwein: The hair brush is a little creepy.

Curt Cornum: Yeah, the hairbrush might be a little creepy. There’s actually, I was just talking about my bathroom scale in the article which I won’t bore you guys with the details. I won’t even say it was borderline creepy. You can go read it if you find it out there. But I think all of those things are changing business models and they’re changing the way that we all try to experience things.

Dan Gutwein: You’re spot on, it’s about the experience and I haven’t met anyone yet that dislikes the frictionless Uber experience when you leave the car. You just kind of walk away. I haven’t met anyone yet that says, “Man I really want to give this guy my credit card and let him.” Remember the old days [card swiping sounds]. So it is about the experience and I think when you’re heading into a store and you’re looking for a product and they actually have it. You’re not having to be hunting for it forever, have it where it is, and you can touch and feel is a great experience. If you’re going into a hospital, having you move through that hospital, not sitting around forever wasting time is a good experience. We’re tracking thousands of pigs, swine in North Carolina right now in a pilot project. Because we know that, we’re actually tracking the feeding trough and I think not having swine flu is a good experience. And so we know that if they don’t eat at certain times, that they’re sick. And I think those are good experiences. And I think those aren’t creepy experiences, they’re enhancing the way that it is. And I’ll tell one CES story and then I’ll be done. I was at CES this year as well and there was a sign there at one of the booths that will go nameless. And it said, “Talk to your refrigerator.” And I asked the guy standing there and I said, “What do I want to say to my refrigerator?” And he said, “Oh, watch this. Refrigerator, what’s the temperature in Minneapolis?” And the refrigerator came back and told the temperature in Minneapolis. And I told him, “Look dude, if I ever get to the point where I’m having a conversation with my refrigerator, I have other issues. But again, somebody might like that, I’m just not their target audience. I would love it if my refrigerator were to send me a note saying, “Hey, we’re out of milk.” Or actually send that order off to Amazon or whatever online grocer and just have it done. So there are some IoT things gone bad, there are some weird things. But again, you’re looking at a sample of three, not the entire consumer world and I think somebody might love having a conversation with your refrigerator. I don’t want to I guess.

Robyn Itule: Given the conversations that happen in my kitchen with two preschooler/toddler that refrigerator is going to be responding to some very strange requests.

Curt Cornum: Yeah exactly.

Robyn Itule: Which is very interesting data and might have some predictive analytics for their choices when they’re older. I don’t know but these are the realities we are facing in a real-time and Internet and/smart things environment. But underlying all of that, the experience sits on a number of platforms. And a certain amount of expertise has to be applied there. We’ve talked about how complicated it is. It is not necessarily that you just make something smart. In fact, we argue, some things really maybe shouldn’t be. Perhaps a refrigerator. Maybe we’ll be proved wrong. History will have to bear that out. But what capabilities does an organization need to build up if this is a really strategic objective for them to deploy.

Bob Familiar: Well just starting on that, the technology side certainly is this area of Dev Ops. So you have to know how to automate your entire software development lifecycle. You are now in the software business. SO you’re going to have a connective product. It now becomes all about the data. So data, it’s going to involve data stores, it’s going to involve analytics, it’s going to involve various services and applications. You have to know how to manage that in a cloud environment and do it for leveraging what’s called multi-tendency. Which means you’re building software applications that both your employees as well as your partners and customers are all authenticating into. The same cloud hosted software. So you have to know how to manage these multi-tenant identity environments. On the other side, its impacting your business model. So you’re not necessarily now selling this product, you’re selling an experience. Imagine that rippling though your organization that now you sell an experience. And what impact that has on your public facing website. So your entire digital experience through your mobile applications, your sales force, the marketing team. And of course, as I spoke about earlier, IT. So it has these profound impacts on the culture of your organization. That’s why, when we engage our clients around here, we like to say well, let’s start with a minimal viable product. Let’s create something that we can operationalize quickly and through that process, your IT folks, your developers, your operations teams will learn about how to do Dev Ops and how to build these applications. We’ll work though that and obviously engaging early your customers so that they’re now providing you feedback on the experience and then your sales teams, your marketing teams can all learn from that. So the whole point is don’t try to boil the ocean, that you use what we like to call lean engineering approach, and you bring these minimal viable products to market quickly at velocity and though that process learn internally and have your customers then provide direct feedback that you can then iterate on the next version of that, and always stay on target with what you’re bringing to market.

Dan Gutwein: I think you’re spot on right with that. I’ll take a little different direction on that. I think maybe, businesses organizations probably need to look at how they’re spending what kind of budget that they’re allocating towards connecting things towards that as well. I had a conversation a couple days ago with one of our field sales persons and they want to know how much does it cost. Well going out to your customer and requesting a quarter billion dollars is probably not the right way to start because it’s going to freak everybody out. This company spent well over that doing cloud applications and the like. But I think even maybe even as an industry, as a technology provider industry, we might need to relook at how we’re going to market with some of this as well. Because the world has changed. Going to go out and suck cap x budget dry [assumed]. When maybe it should be more into an op-ex piece, more the services model with something that. I know at least in our group, we’re considering very heavily at Intel, we’ve got to make this to where, it’s even difficult for large companies, even if there’s a guaranteed increase ramp in sales, to come up with a cap x early up front. So the business process really from the company side, I think really from the technology provider side, has to change a little bit too. And I think all of us can share in the benefits of satisfying consumers. But I think probably a little different business model like internally in the business community too.

Robyn Itule: Curt, you spent a lot of time with our clients in philosophical conversations but also practical ones about how to get started. Where does that conversation typically begin for you?

Curt Cornum: Well its interesting we mentioned, we talk to a client and they kind of understand now that they need to go a direction that they haven’t before. And sometimes we can learn from the past. If we look back, probably 16,17 years ago, the things that a lot of folks call operational technology like the voice systems were one of those. They were very much siloed, pretty much an OT type of thing. And then as voice started getting IP enabled, it eventually became an AP function and you had IT folks that were like “We don’t know these voice systems.” And you had the voice people going, “This is my domain, don’t mess with it,” And we’re seeing that a lot these days. So I think it’s a transition. I think we’ve learned in the past that these things are going to happen and as they become more digitized that it’s an opportunity and a challenge for folks in IT to embrace this. And I would say that we hear a lot, I’ve done a lot of infrastructure over the last 20-30 years. We hear a lot about software eating the world. Because I think as I mentioned, the star of the show really is the software and the analytics and all of the power that we’re able to draw insight in from now. There’s still an underlying infrastructure there. And so I brought you something for a little show and tell. This is my Raspberry Pi. And I don’t know if your kids have one of those yet, but you’re never too young or too old to learn how to code, Raspberry Pi is actually foundation. And that little thing, the base price on it is around 35 bucks. That one I suped it up a little bit, but its packed with sensors and it has a real-time operating system and all those kind of things; full blown OS. I actually had it talking to Watson last night which is way overkill for what I’m doing. But I’m trying to get back to my roots and learn some code because a lot of what we are talking about here is driven by things like Python and Java Script and those other things. And its pretty intimidating for a lot of folks. But when you look at the way these platforms are designed today, they really do kind of guide you through this process and make that IoT stack more digestible for a lot of folks. So I think its one of the simple things. You need to understand that stack and do a minimal viable product, start small, maybe keep it in a silo and then look at the integration after you look at the proof of value and those types of things to get them into environment. But I think it is kind of a crawl, walk, run type of thing for IoT.

Curt Cornum: We’ll be back with more of our Internet of things livestream in just a minute. Stay with us.

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Robyn Itule: So as we wrap this part of our conversation, we’ve done a lot of reflection on what has come to pass. There is actually a pretty lengthy history around IoT. Things have been cognified for a while now. But where do you each see real time business going? And I’ll give you a really short tweetable amount of time to answer that question for our listeners.

Dan Gutwein: Go ahead Bob.

Bob Familiar: Well I love what I’m seeing today. This combination of the IoT platform approach and the applications we build for data visualization and remote monitoring. That’s becoming fairly mature. But now it’s the integration of artificial intelligence. Its bringing in these very intelligent chat bot applications to be integrated with the real-time data creating again these really cool immersive intelligent experiences for the end user.

Robyn Itule: Dan?

Dan Gutwein: Yeah, I think I would just simply say environments that are created to respond to you, to the consumer. And that’s not far out in the future either. When I walk in the store, why can’t that store respond to me as I want them to respond to? As I walk in the store and I’m a VIP loyal customer, and I want to grab my jeans and walk out, why shouldn’t I be able to do that? And having what I want, when I want it. And it’s, by the way, if you think we’re asking for that, just wait until your kids become massive consumers. Because you’ve got a lot of research on the next generation and that’s exactly where they’re headed. They’re in a very connected world and I think that its going to continue that. Probably not tweetable but fire away.

Curt Cornum: I’ll make up for him. I mentioned before its that integration of the digital world with the physical world and making that much more seamless. So as I go places and I try to make decisions about things, I can leverage what I know from the digital world and apply it to the physical world which is still where we all exist today.

Robyn Itule: Still, it feels like you’re leaving some question.

Curt Cornum: Well I just got done binge watching Westworld on HBO on demand, so I’m starting to question what’s real and what’s not these days. So thanks for having me as your new guest host and thanks for trying something different with us on Technomics today. Like I said at the start of the show, we have many more Technomics coming up in the next couple of months and we expect to hear more great episodes like this one. And hopefully you enjoyed having me, I definitely had a great time today. So thanks again for listening to Technomics, and we’ll chat again soon.

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Robyn Itule: Thanks for listening to Technomics. If you want to find more episodes, you can download the episodes from iTunes, Google, or your favorite podcast provider. And for more stories on intelligent technology, visit www.insight.com

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