In this episode, Rob and Josef talk about the impending paradigm shift represented by the metaverse, and relate it to past shifts.
They speak with Joe Sriver, the first UX/UI hire at Google, founder of the cellphone flashlight function, and CEO of 4giving. Joe talks about the importance of being data-driven as an early employee at Google, and as a founder at one of the first app store developers, DoApp.
Who does Joe Sriver see executing? Pipe.
Welcome to the execution is King podcast where we talk to successful startup founders, investors and ecosystem builders to cover insights and best practices for the next generation of great global startups. Today, we’re going to be talking with Joe Shriver, CEO of forgiving. So Rob, Facebook recently rebranded as meta, and everybody is talking about the metaverse, and not a lot of people quite know what it is yet. But we kind of sense that something bigs happening like there’s this big paradigm shift, what was your experience, like in previous big shifts like this? So paradigm
shifts are really interesting. And with Joe, on our podcast today, you know, we both went through a couple of these. And you know, one of those was kind of the initial advent of the internet in the 90s and early 2000s. Him at Google, and then his own startup do app for the iPhone. You know, for me, it was kind of publishing my own websites. And then kind of within the business that we had created launching a business on for iPhone and Android in the early 2009 2010. But, you know, it’s interesting, when you’re designing a startup, or you’re thinking about a startups kind of strategy and roadmap, when you have these paradigm shifts with new platforms, you have to think about what’s the killer app going to be for startups that are going to compete with me in my vertical. And there’s all these kind of first mover advantages in terms of network effects or switching costs. So you really want to think that through early, because the that first mover advantage can be can be hard to unseat. And we’re in and I think about that, like, you know, it’s actually been 13 years since the iPhone shipped, I think it was 2008. And here we are in 2021. And we still it still feels very much like for mobile compute. We’re still like in the second or third inning, there’s still people dreaming up, you know, a new mobile app kind of first use cases that are completely dominating verticals. And so and I think we’re still like in the early innings of the mobile compute. But now we’re probably, you know, 234 years out from the, you know, this new Metaverse world. And, you know, imagine what the world is gonna look like, when we have a billion users walking around with smart glasses over their, over their eyes, in leveraging, particularly, I think the augmented reality use cases. So I think that’s, it’s just really interesting to think about. And I think, you know, the real pioneers that jump on these paradigm shifts early, there’s many examples of them who sort of roll that those waves to just multi billion dollar kind of outcome, Joe talks about what it was like going from designing web experience at Google. And the interface is to, you know, simplifying things for a small mobile screen and the importance of simplicity and data, and really both those examples, but especially in a small screen factor. You know, imagine that, for what’s needed for a full three dimensional context to wear glasses experience, I have no doubt that there’s gonna be like a whole different breed of applications that are like things we’ve never even seen before. Joe, for starters, can you tell us a little bit about your background kind of through your career and just introduce yourself for our listeners today?
Sure, yeah. Thanks a lot for giving me this opportunity. Appreciate it, Rob. So I began my career. After college at at IBM before college, I was fortunate to work as an intern at Intel Corporation, that kind of gave me a path for my future career. So I was at IBM for about three and a half years. And in Rochester, Minnesota, it’s down south from the Twin Cities. Then I was fortunate to move on to Google as their first UI UX employee. And that was in I was hired in 2007 2001. It was there for about five years. Then I moved back to the cities and started a company with a couple of guys that I knew from my days back at IBM is called do app. And we were fortunate to be at the forefront of when the mobile technology started taking off with the iPhone and Android devices. We had kind of three companies within do app. And we were fortunate to have three exits through do app. After after do app. Then I met a guy down in Rochester, that was working on a fundraising software platform. And actually during do app, I had some ideas around the fundraising space. So this guy had some stuff going on already. I joined him and that company is called forgiving them at forgiving right now. And we’re having a great time.
You were the first UI UX hire at Google. I mean, I I envisioned you walking into the garage, but I suppose there’s a few more employees than that at that point.
I always think of that. So the group I was at at IBM obviously IBM is a huge company. and still is, the group I was at IBM had about 200 people. And so then at the time, when I joined Google, they were just under 200 people. So I thought, Oh, it’s just, you know, kind of a lateral move, you know, to another group of 200 people. But by the time I left Google, it was, I think, was probably about 10,000 people. And I have no idea what they’re at now. But at the time, I didn’t think it was the early days. But now looking back, it was the early days of Google. And so it was exciting just to be part of that. I know,
we’ve known each other for a few years, Joe, and as an entrepreneur has been building software companies, since I was 15, like, you know, 25 years or whatever, I think maybe a lot of entrepreneurs and feel like myself, where it’s just like you dream of creating a company, you know, to the scale of a Google or an Amazon or an Uber. And you guys, quite frankly, I think it’s really interesting, because so few people will ever get a chance in their lifetime, to have that kind of an experience. I mean, there’s just not that many companies that are the most valuable in the world that are getting started. So would love to learn more about, you know, some of the takeaways,
one of the big takeaways from my experience at Google was just their focus on collecting data and making decisions from from the data that they’re collecting. And that was one thing that I’ll be honest, I didn’t really think about too much before I got to Google, like, for my Intel, or IBM days, but they were beginning to that. And it got that kind of semi course for for future endeavors at do app as well as forgiving. I mean, having data drive, the decisions that we make, one of the projects that Google I was involved with, was just the look and feel of how ads appear on the search results page. And now they’ve kind of gone away from the ad look and feel still somewhat similar these days. But they used to have ads on the side of the page, those were what I was responsible for kind of designing the look and feel. And just, it was just always interesting to see small changes, like you know, bolding text, or putting a line here or horizontal rule there, or just the color of the background or the size of the font, just how much of a massive change that would create as far as revenue coming in, they would do these experiments, they call them 5% experiments where they just took about 5% of their traffic. And they would put them through this kind of experimental UI route, when they’re searching pages. At the time you 5% was still a large number of folks that were going through the pages centrism, to see how just these A B tests that would that we did back in the day, how much of a change, you know, just like I said, little things in bold in text, you know, putting a horizontal rule here or there would change the click through rate. I forget the exact numbers. But then I mean, it was like millions of dollars, you know, more revenue on a daily basis that they’d be getting just with these little changes. So and that kind of, like I said, Said, set the course to look at data and do app as well as forgiving. We may not have the amount of users and people I think those those experiments, and a B testing is still really important. So you
end up going from from Google, in one have known at the time, of course, but went on to become the one of the most valuable companies in the world. And then you leave and you go found your own startup in do app, what was going through your mind at that time when you decided to leave Google? And what was sort of the original idea and plan for
sure. So so after Google, I was kind of in the heart of technology in Silicon Valley. So I came back to Minnesota, I thought maybe I was kind of on my own as far as tech startups and startups in general. But I still kind of like that, that startup feel and entrepreneurship. So in about, I think, to the end of 2006 or so I started a company at the time was called Page Powell. And it was a focus on just widgets like back then with with blogs and stuff, there’s like, you know, little widgets that you put on, like your blog to, you know, tell whether our stock boats, but I was actually working with a group of developers in Hopkins, Minnesota got to the point where I thought maybe I should bring this in, in house, I tap my buddies that I met down in Rochester back in my IBM days, Wade beavers, and Dave worrilow. And said, hey, you know, we talked about different bunch of different ideas when back in the late 90s. And are you at a point in your career to, to jump ship and join me on this startup? Right. And unfortunately, they were they were excited. So waiting, Dave came on board and, and wait, and David had some experience on mobile stuff that they were doing for for IBM, I think on BlackBerry or the mobile technology of the day, then in the late 2000s. And they said, Well, you know, we’ve been experimenting with mobile at IBM. And I think that’s that’s the future and fortunately, around that time, I think it was I think it was in July of oh seven or interval seven word the iPhone came out or debuted. And then in oh eight, spring of all ages when the App Store debuted, or maybe in July of oh eight I’d have to look back Anyway, so we were fortunate at do app, we kind of jumped ship from the widgets. I forget the numbers. But I think the initial developer pool for the App Store was maybe 500 people, or 500. Developers. And we thought, you know, being in Minnesota, we have never had a chance. But fortunately, Apple picked us. And we had exceeded three of the first, either 500, or three of the first 1000 apps so that we were very fortunate. And actually, one of the apps that we had was a flashlight app that because it was my old flip phone that I used to search around with, had my phone on to search around for stuff in the dark. And I thought why it’s good to have a white screen on the iPhone and make it into a flashlight. And so actually, that app during the course of do app was actually probably one of our most popular outfits. Even after they they had that flashlight on the back with the flash on the camera. People were still downloading the the highlight app, as we call it. Actually, at the beginning, we had a slew of apps and a bunch of different verticals. We had some game apps, we had some utility apps, like the highlights and some other random apps. And so Wade had the foresight to kind of start focusing, we had a contact at WCC o in town here. And we’re able to do a news app for them. So we that got us kind to the news and media app. Dave had some experience in real estate. So we start down a real estate vertical. Being that basically half our team was in Rochester, Minnesota, they had some contacts at Mayo. So then we had some medical and vertical. So we were essentially planted in three different verticals, medical, real estate and media. And eventually, we found a way to exit all those verticals. So the first was the medical vertical. That was a deal that we had with the Mayo Clinic, we were kind of 5050 in that and we sold it to axial exchange, I think was the company that we sold it to. We sold the medical in 2012. And then in 2014, we sold their real estate apps that we developed to a company called core logic. And then in 2016, we sold the news app that was sold to a local company in Minneapolis called new cycle and now it’s called naviga. The news news apps and I think the real estate app still exist in some form.
Did I hear in there that you invented the cell phone flashlight,
that it was called the highlight? I think it was basically the first kind of flashlight, which was I mean, it was a flashlight, just that the screen was white and couldn’t find things in the night? Yeah, I think that was the first flashlight in the in the App Store? I’d have to look, I haven’t I haven’t searched the app store recently. But um, I think it’s might still be in there.
Wow, talk about identifying a real need. Right there. Right?
Yeah, I just love this story. Joe, I’ve had the, you know, the fortune, the good fortune of kind of living through a couple of major compute paradigms like, you know, the birth of the Internet in the mid 90s. And as a, you know, teenager launch, you know, publishing websites, you know, right after, like, Netscape browser comes out. And you know, that just excitement, you’re just sort of when you’re that early into life, or like, I know, that’s around the time on the App Store, when you and I met I believe in, you know, we just sort of like use when you see these new kind of particular consumer platforms emerge. You know, there’s just like, so much buzz and excitement to be there early. And part of it is it’s the not knowing, right? It’s not always like this super linear path of like, what are we going to use the iPhone for, you know, from a flashlight to a help app to real estate listings or real estate apps to, you know, that ultimate, I think, was the news app business, kind of the most successful of all that. And then yeah, but like, I see that now. I think a lot entrepreneurs are sometimes, you know, maybe late adopters, and they kind of let the dust settle, but some of the real pioneering work that comes on these compute platforms. And of course, now I see that there’s always, you know, it seems like now we’re talking about Metaverse, and we’re talking about the, you know, things that are happening in VR and AR and Oculus. And it seems like, obviously, the large investments into the hardware with like smart glasses. And like, it seems like a new form factor that may eventually make its way would be the smart glasses, but it creates almost like a completely different product design. You almost had to invent it as you go, right? Because no one really knew how to design a smartphone app. You know, at the time you guys were working, right? How did you figure out even like, what to build, or what kind of UI and UX patterns to kind of use.
We had a strategy session early on, and we had like a list of hundreds of app ideas. But then actually, at the time of before the App Store came out, you could jailbreak your phone and and there’s like some, like, full kind of app stores on on the internet. And we were searching those and we thought you know, all these ideas, hundreds ideas that we had, you know, were unique to themselves. But um, we looked at these Jail Break app stores or whatever they were called. And we saw when everybody has the same fan list of ideas that we have, and the UI stuff. I mean, I personally I think of myself as a UI designer still, but the whole kind of spaces completely expanded with even even within the space, like I mean, just different designs, you have to create for all the different browsers plus the mobile browsers, the more different mobile phones. And it’s just just to kind of a headache. When you start thinking about it. You’ve had
this experience working as a part of a number of teams at Google and then some of your own entrepreneurial endeavors. And you kind of talked about the this importance of in your, in the way you were building your teams, as you’re telling the story about actually having, you know, practical experience working with a lot of the people. Can you talk a little bit about that, and you know, what’s gone into building your teams and some of the lessons that you’ve learned, I think
the strategy that Wade had, that I that I’ve tried to follow with forgiving is just, it’s just kind of finding these these people that you work well with. And one thing I didn’t realize is in Silicon Valley is that like, kind there’s the these groups of engineers that how are they met, maybe they met at school, or maybe they met at a different job, but they, they kind of go around in groups like to different people. So I noticed that after Google, like tiny groups of people, like in those project manager, as well, as engineers, they kind of went as a group down to like Facebook, and, you know, wherever else. And I thought that was kind of interesting concept that once you find a group of people that you work well with, and kind of, you know, their ins and outs, and it’s interesting to kind of follow them to different startups. And so I think that’s kind of what I tried to do. I mean, I knew Pete and Jim Well, and so I asked them to, if they would mind coming to forgiving, and they did. So I work well with them at do app, I’ve been fortunate to find the chi in my group of people. And
that reminds me of Silicon Valley, there’s an episode where they’re at Hooli. And I forget who the CEO of Hooli is, but he’s like, looking out this window in commenting to his assistant that, like the developers always travel in packs. And it’s like, judging them by you know, they he’s judging them by appearance. That’s right. Yes, or No, I remember.
Yeah. Yeah. That episode, yeah, with Gavin Belson. But yeah,
I think you see these. Yeah, it’s interesting to hear your story. And, you know, I see these patterns, you know, as an investor, and then in my own operating experience, or entrepreneurial experience, to see these patterns. And this pattern of sort of, in other worlds, and really short supply of people that know how to build digital products and do it at the highest levels, whether I’m building a product for my own business, or I’m an investor, I always kind of observe, you know, take notice of who I think are really the like the top performers that are working really well. And I sort of, I just sort of take note of that, for the rest of my life, there are people who worked with me 10 or 15 years ago, maybe even for less than a year, who I always make it a point to check in with them, like a couple times a year, because I always want to work with them, again, the kind of people who can blow you away with their execution, it could be on you know, like the software development could be designers, could be even sales or marketing talent, when you have a chance to work with someone like that you like you kind of want to spend the rest of your time figuring out how do you get them back in your orbit, so you can work with them again. So I think this kind of clustering makes a lot of sense. Because, you know, there’s just so few people that have those kind of execution abilities. And then you know, I think once you find them, and then you work, well maybe have a similar like cultural values, there’s, that kind of seems natural that you’d see these clustering. And I guess that’s probably an importance in hiring. Like, if you don’t have that kind of a network, then maybe your first few hires are going to be so important, because they’re going to lead to the next hires. And so if you find people that have been in really high performing teams, they’re going to probably want to bring their friends to come work on interesting projects, right. So you know, that real estate startup, that’s probably, you know, if you’re doing it for the first time, you don’t have that kind of a network, you know, maybe you can try to it’s so important to get those first hires white, right, because it can kind of lead to almost like a domino effect. Right.
Right, right. Yeah. So if we’re given we’re pretty small team, there’s actually just four people that are full time. And but but yeah, at some point, we’ll probably have to hire another developer, and already, you know, has a list of people that he knows that he trusts and knows, you know, similar work ethic and coding ethic that that he does, and so, so yeah, so you’re you’re absolutely right, that you kind of rely on on the kind of, you know, your core network, but then you’ll people know people and kind of expand out from there. So,
yeah, that’s super relevant. Now. i The first thing I saw on LinkedIn today was an article about procuring tech talent and competing for it effectively, because I mean, the job market right now is incredibly competitive. But after all the recruiting and all the LinkedIn posting and everything falls away. That’s kind of what it comes down to. Is these relationships. Joe? Can you kind
of describe for giving you know what was the original idea behind it. And also talk to us a little bit about how this is gonna benefit the philanthropy world going forward. Sure. So
yeah, so the ideas that I had regarding fundraiser when I was back at do app, and we are already in three different verticals, so fundraising didn’t turn out to be one of them. But I’ve been fortunate to be able to go to different galleries and events and fundraising events and kind of looked at the software that they they’d have, and like, you know, this is, you know, it’s gonna be a lot simpler. And so when I joined forgiving, it was about a, approximately about six months or a year old when I joined, I think before giving started in late 2017, I joined in mid to late 2018. And at the time, it was just the founder and he had outsource the development work to, to team that he knew. So then that’s when I brought in Pete, the developer that I said, you know, we need to bring the development in house, we can’t have a outside vendor doing it. So we brought it in house I hired Pete, who was a developer, I met that do app that’s still with us. And we started creating stuff alone, actually, at the time, I was kind of, right, I really thought that I could take on the UI stuff as well, and I did for the first few months, but I thought you know the skin too, too much. And with with other SEO type stuff that I do. So then that’s when I reached out to the gym. So he came on board and has done a great job to take over the UI stuff. So
before giving how many nonprofits are currently using the platform, and the main functionalities are kind of centered around payments and kind of marketing to donors or what some of the core functionality you all designed.
Currently with forgiving, we have approximately about 350 to 400 nonprofits and organizations using the system and, and the kind of goal behind forgiving was just to make it really simple for a nonprofit to get up and running on their fundraiser. I mean, the the nonprofits that we talked to are generally small, they have maybe two to five people on their staff, and most of them are probably part time, or they’re they’re just volunteering, they’re not even part time they’re volunteers, they don’t have time to figure out, you know, a new fundraising software. So that was kind of the point behind before giving is make it ultra simple for persons go in there quickly get a fundraiser up and running, he will share it on social media, by email or whatever,
I see a cultural issue kind of in the middle of the country after spending time in San Francisco with my last company, the lack of perceived value of equity. No, for one, we hired a lot of people here in a few in the bay area as we built up our office. And I always tell this story that, you know, we had, let’s say hello to 350 people in Minnesota. And I think I only had I can only think of a couple of times where any employees we hired really negotiated their equity packages. And then conversely, that this is a sign of the culture like in San Francisco, I think every single employee we we would hire, negotiated their equity, even not even like our administrative staff, like a receptionist or whatever. And I thought this is so different. Like it shows you the negotiation of your equity package, it sort of shows you the value that that is perceived to have.
Right? Well, yeah, that’s one thing after I left Google, that I didn’t know going in there is that, you know, I could have said, hey, I’ll take you know, X dollars less for my yearly salary for you know, more equity. And I obviously looking back, I probably should have done that. I didn’t even know that you could do that. The other thing is that I didn’t really have much money to I mean, yeah, Silicon Valley is an expensive place to live. And I’d rather probably have a place to live than, you know, equity. That may not mean anything I do I have several friends that worked at I forgot what companies this one particular year, I worked at, like three different startups, where the equity eventually went to zero because the company fell or whatever. And then Google was the winner. But I was certainly fortunate to be on that ride for for as long as I have in Vegas. I’m technically still on that ride.
Yeah, I think that’s really interesting. I that’s often advice I often find sharing with my friends that are joining early stage companies is, you know, can you go without maybe without a vacation for your for the next year or two and like maybe maybe you can get, you know, 50% more equity if you just accept 20% lower base. Or if you did that throughout your whole career, like usually the compounding nature of the equity returns is going to be like life changing for you those little decisions. Like I know everyone has different personal financial situations or goals. And we don’t most people I don’t think are really building startups just to make money. They’re building it. You know, I imagine in the case of forgiving like, death three to help simplify the fundraising process for 350 or 400. Nonprofits. It’s gotta be really easy to get out of bed in the morning, right? But I still think like on a on the financial side, it’s just like maybe, maybe, maybe just to think a little differently sometimes like, I don’t know, for whatever reason, I just find that to be a challenge sometimes here like I mean, It’s just like the corporate mindset that kind of dominates. You just don’t have the you don’t have the stories of the equity compensation really becoming kind of life changing. And hopefully that’ll continue to change over time as we have more and more big exits and whatnot.
Right? Yeah. I mean, it’s it’s kind of what stage of life you’re at. I mean, I was single when I moved out to California. I mean, if I knew better, I would have said no, less salary for more equity. But, um, but But yeah, I mean, when do we have a family? You know, obviously, you need to pay for food, housing, whatever. And, you know, the life circumstances change? So,
do you have any advice for new founders, Joe, whether it has to do with like, baking in this data driven approach, or negotiating equity or anything like that.
But as far as future founders or even just even if you’re not in to the entrepreneurial mindset is, this some stuff that we touched on before is just like finding the group of people that that you’ll maybe eventually kind of go as a group to different different companies, I don’t think anybody is probably going to be at the same company, their whole life in the tech industry, at least they’re, you know, you’re gonna probably be at multiple companies, it’s not going to be like, my dad, who was at his company for 40, or however many 45 years, just kind of finding that group of people that you work well with, and you trust and, and there’s integrity among Hmong, everybody. And the other thing is, as far as entrepreneurs, I think finding ways to get yourself out there, it helps you, I think you hone your hone the product and be able to explain the product that you’re working on a lot easier. And being able to communicate with your team as well as outside individuals, whether you’re going to investors for capital, or whatever, it’s to be able to, you know, have those communication skills.
Who do you see that is really executing right now? Are there any founders or a company? Maybe people haven’t even heard of them? Or maybe it’s Google? Who knows? You would have the inside insight on that. But do you see anybody right now that’s really executing?
Everybody I talked to, I think, Oh, I yeah, that that’s really great. I never thought of it that way. Or I never thought of a product like that. And, you know, I want to invest in it. And I can’t I mean, that I have to force myself to go through some other criteria to, to narrow down my list. But one that I keep on going and going going back to my mind is a company called pipe. And they had this product where a company can they work with, like larger companies who have recurring revenue, but like the recurring revenue, if it’s like, I’m not gonna explain this really well. But yeah, if the recurring revenue is like $10,000 a month, so that means like, $120,000 a year, well, this pipe company will match you with an investor that will pay you the you know, the upfront $120,000 for the whole year, so then you can start investing that in different initiatives that you want. And then obviously, the investor gets a little cut from that that idea might have been around for a while. But I just thought that was an interesting way to help help other companies.
That pipe company is so interesting, because I think you’re right, I think that financial model of providing almost like a loan product against future recurring revenue is sort of been around through service providers or financing companies for maybe a while, but he, he productized it in a product to scale, it actually becomes a really disruptive force for like, say, the SAS kind of VCs who, you know, in the past can make these really relatively safe investments, because of the predictability of the cash flow, the effect that would have in diluting the founders equity was pretty, pretty, pretty tremendous for a lot of the breakout SAS companies, and now with Greenwood pacement able to do to bring scale to this type of capital. So we’re seeing has the potential to dramatically increase the the founders ability to maintain equity, and maybe maybe early investors as well,
after you said, so yeah, that makes sense. Yeah. I always intrigued by ideas I like Yeah. Why didn’t I think of that? You know,
it’s kind of the mark of a good idea, isn’t it? Where it’s like, why didn’t I think of that?
Yeah, it’s, it’s like staring right at your face in your life,
like a flashlight on a cell phone. Alright.
Awesome. Well, thanks so much for joining us today. You know, I always enjoy our conversations. And he has such an interesting career that you’re on between, you know, the once in a generation kind of opportunity to work in the early days of Google and then then moving on to your own startups. And it’s just it’s incredible to hear, you know, the different turns that you’ve had in your career and to share some of the wisdom along the way. We appreciate you taking the time.
Right. No, I appreciate you offering this opportunity. I read Outliers book by Malcolm Gladwell, which I’m sure a lot of people have and I kind of see that in me that was as well as everyone in scholars were kind of born at a At the right time to be able to take advantage of these opportunities and that continues for everybody.
Sheryl Sandberg joined Facebook in 2008, when Facebook was very small. She was instrumental in its meteoric growth into the global giant it is today. Many people are trying to put blame on her and downplay her work now, but her role and contributions over the years should be celebrated. She was a successful ‘integrator’ at Facebook, working with Mark Zuckerberg.
The EOS (Entrepreneur Operating System) blog defines an integrator as “…the person who is the tie-breaker for the leadership team, is the glue for the organization, holds everything together, beats the drum (provides cadence), is accountable for the P&L results, executes the business plan, holds the Leadership Team accountable, and is the steady force in the organization. The Integrator also creates organizational clarity, communication, and consistency; typically (but not always) operates more on logic; drives results; forces resolution, focus, team unity, prioritization and follow-through; is the filter for all of the Visionary’s ideas; harmoniously integrates the Leadership Team; and helps to remove obstacles and barriers.”
There is a history of visionary founders combining forces with integrators in Silicon Valley at hugely successful companies like:
• Sergey Brin & Larry Page with Eric Schmidt at Google
• Steve Wozniak with Steve Jobs at Apple
• Gordon Moore and Bob Noyce with Andy Grove at Intel.
This is not just a Silicon Valley phenomenon. Local Minnesota examples include:
• Justin Kaufenberg with Brian Bell at SportsEngine
• Ben Cattor with Alex Ware at Foodsby
And I speak from my own experience. Ryan Weber and I co-founded NativeX, and brought Andy Johnson on board as integrator when we grew. It was a difficult decision, but the right one. You can read about in this article I wrote for Wired.
Integrators can be instrumental in carrying companies forward by collaborating with the founders at the right time. A company can be started by ‘singular’ founders, and carried forward beyond 50-100 employees by ‘integrators’. This is why singular CEOs of more mature companies often have integrator COOs beside them. The reverse order does not always work; as remarkable as integrators are, integrators may not be successful founders. Could Eric Schmidt have founded Google? Could Sheryl Sandberg have founded Facebook? You decide!
But don’t forget to also ask yourself, could Zuckerberg have grown Facebook into the global success it is today, without the talented integrator Sheryl Sandberg?
IoT and Analytics – Organizing the Industrial Internet
Figure 1: The third revolution: IoT and Analytics. [Image credit: General Electric]
The Evolution of IoT – Where we Came From
The first generation of IoT systems (IoT 1.0) was built mostly with data collected from IP-based sensors by monitoring applications. Whether standalone or embedded in phones, low-cost sensors, compact packaging and distributed power enabled new endpoints and systems. These monitoring applications served needs such as asset tracking, fitness monitoring, mood lighting, physical security, and others.
The second generation (IoT 2.0) leveraged the capabilities of infrastructure tools such as edge gateways, publish-subscribe buses, data warehouses, and API-based integration. The edge gateways allowed IP network segments to connect to sensor bus segments using a diverse set of protocols (e.g., RS-422, RS-485, BACnet, CAN, Fieldbus, Hart, LonWorks, Profibus, Seriplex, Zigbee, Z-wave, and others). The gateways extended the reach of these IoT systems across the many incumbent protocols and enabled the integration of the IP segments with legacy systems. The publish-subscribe buses made data-driven software architectures easier to implement and scale. The data warehouses enabled the integration of structured, semi-structured and unstructured data. The integration APIs enabled ingestion of data at scale. Together, these new building blocks enabled larger-scale IoT applications such as home monitoring, smart metering, power grid management, parking systems, next-generation environmental controls in buildings, windmill farms, warehouse management, etc., with varying degrees of commercial success based on the benefit provided vs. the insertion economics of each use case.
With the larger data sets enabled by frameworks such as Hadoop and big data software such as Pivotal, the third generation of IoT systems (IoT 3.0) is integrating analytics for decision-making. These analytic platforms enable the processing and visualization of the IoT data sets. The large data sets and analytic tools identify aberrations with higher levels of confidence (statistical power) and detect ‘signals’ not seen before, they have lower detection thresholds, greater measurement sensitivity, and higher accuracy.
Applications based on these capabilities range from physical security for homes, buildings, and warehouses; to detection of diseases like lung disease, cancer metastases, or cardiac arrhythmias (see the Mayo Clinic and AliveCor’s recent work); and complex chemical analysis as in rare earth element detection. The availability of computing platforms at the ‘edge’ (e.g., gateways) enables distributed/local analysis.
“The Internet of Things is giving rise to a tsunami of data,” said Great North Labs advisor Ben Edwards (founding team member of home automation pioneer SmartThings). “The billions of residential sensors in people’s homes and the personal sensors on their bodies are sources of data of value to each of us, and depending on what we make available to others, to family members for our safety and well-being, to the retailers we buy from, to the health practitioners who take care of us.”
The proliferation of machine learning algorithms with new programming environments such as Python and dataflow libraries such as TensorFlow has opened up a wide range of new applications. These include anomaly-based security alerts, health and fitness monitoring, genomic analysis and biomarker detection for disease prediction, drones, and self-driving cars.
The addition of machine learning libraries to established platforms such as Matlab, R, SAS, and SPSS, is enabling insertion of machine learning into legacy applications.
The availability of these tools in public and private clouds has made their accessibility and deployment even easier.
Together, with supervised and unsupervised learning, the machine learning software is processing data sets with high data dimensionality, like those from mining, voice processing, drone navigation, and self-driving cars.
The integration platforms and IP-based communication are also enabling the integration of the IoT world with the enterprise world, making applications possible across hybrid computing and control environments such as airports, buildings, cargo ships, factories, hospitals, refineries and oil rigs. While this creates security issues for the enterprise as well as control systems, solutions such as micro-segmentation of hybrid systems are beginning to emerge.
Tomorrow – The New Startups
With products from companies such as Nvidia, Intel, Qualcomm, Broadcom, and now Google, real-time computing power is becoming available at the edge. With easier integration and low cost, it is becoming embeddable at sensing endpoints for applications such as drones, self-driving cars and trucks, personal walking/talking robots, personal assistants, point-of-care diagnosis, no-POS retail, smart logistics, and smart city applications from parking lots to secure airports and intelligent highways.
Beyond analytics and monitoring, this fourth generation of IoT systems will be able to use analytics and machine learning for controls.
What is the outlook for the adoption of these applications? The answer is: it depends. And it is best found through analogies.
How confident do today’s chess masters or masters of the game of Go today feel betting against the machine? IBM’s Deep Blue computer beat chess champion Garry Kasparov in 1997. And as Great North Labs advisor Mitch Coopet (CEO of AI-focused Aftercode) points out, “Since 2016, Google’s Alpha Go platform has won against several Go masters using improved deep learning techniques.”
Or, when will the day come when your x-ray machine will have better diagnostic accuracy than your radiologist? Ahem, that day is already here.
Or, when will Alexa be able to detect tonal infection to assess mood? Based on indications from Amazon and makers of social robots and AI assistants, sentiment analysis will progressively improve the way machines will interact with humans.
Or, when will we be comfortable with self-driven cars? Completely autonomous navigation in 5-7 years may be unlikely, but it is equally likely that in 20 years, self-navigation will become a required safety feature for new cars.
Given the range of answers above, it is not a matter of if, but when, that real-time control using machine learning will be common. These systems will be able to handle use cases as diverse as (i) detecting rare earth minerals to help navigate the earthmoving equipment towards richer ore in a mining operation, (ii) making real-time sweeps at airports to pinpoint explosives across large masses of people, luggage, and infrastructure, (iii) ensuring that the robots deployed in automotive assembly stay within the extremely tight tolerances of frame construction, and (iv) predicting the failure of a component in a high value CT scanner or remote ATM to dispatch the skilled repairman in a timely way to avoid downtime (a business that Great North Labs has invested in).
The Innovation Ecosystem of the Industrial Internet
“Business Insider projects that there will be 55 billion IoT devices operating in the world by 2025, impacting a broad set of industries including automotive, consumer products, electronics, medical devices, and industrial equipment,” notes Great North Labs advisor Robert Bodor (Vice-President and GM, Americas, at Protolabs).
At Great North Labs, with an ambitious vision, we aim to help build the innovation ecosystem of the Industrial Internet visualized by IoT 3.0. This is because we believe the ingredients to build it are uniquely within reach for us.
The three pillars of any tech-enabled disruption are entrepreneurs/developers, adopters/enablers, and capital.
- Entrepreneurs/developers. The Upper Midwest created the industrial enterprise. Companies such as 3M, Caterpillar, Emerson, Ford, GM, Honeywell, Johnson Controls, Rockwell, Toro, and many others, have been in the industrial enterprise as their core business for several decades. Their alumni understand the problems and opportunities of the industrial enterprise unlike any others in any other region of the world. The hungry entrepreneurs studying machine learning, paired with vertical experts who have worked on these problems, comprise the ideal startup teams to build the IoT 3.0 applications. The Upper Midwest uniquely provides this talent.
- Adopters/enablers. While the industrial enterprise companies themselves may have limited appetites for leading innovation, they understand that market inflection is around the corner, and they are prepared to have their customers lead the way to achieving market alignment. Partnerships with these companies through co-investments, pilots, and sales affiliation to reach their customers and insert the innovations with minimal risk is the most effective path to adoption.
- Capital. Channels for entrepreneurial capital include venture funds, incubators and accelerators, and corporate investment funds. Of these, we believe that the first two provide the most efficient path for innovators, and that they create the on-ramp for in-house corporate teams to acquire well-formed companies that have demonstrated a strong product-market fit and, through later-stage funding, have even scaled their businesses. The Silicon Valley startups of yesterday that comprise some of the biggest market caps today have done exactly that. We believe that over an extended period, the Industrial Internet can deliver similar outcomes in the Upper Midwest.