Feb 7, 2019 | 5 min read

Conversation with Rick Bullotta

Podcast #45: From Genesis to IoT Big Bang

Rick Bullotta founded two companies that have been pivotal in the development of Connected Industry: Lighthammer (acquired by SAP in 2005) and Thingworx (acquired by PTC in 2014) and he is now an adviser to Microsoft Azure IoT. He’s a passionate advocate of new technologies and innovation, and enjoys the disclaimer that “80% is fact and 20% is BS - and I don’t know which is which”. Our conversation explores his personal background in industrial technology, and how the insights gained from his experiences at Wonderware helped shape the vision for the companies he started. Exploring the genesis of Lighthammer and Thingworx, the discussion touches on why blue collar tasks benefit from an IT-driven “multiplier effect”, how innovation comes from empowered customers, and how simple visibility can kick-start profound changes in industrial businesses. Other topics covered include the market landscape around IoT platforms, potential of AI and machine learning, the possibilities and pitfalls around blockchain and the future of Connected Industry. Areas of particular interest in technology include meta-sensing technologies around drones and robotics, simplifying the last foot of connectivity, 5G technologies and a company called Waveio.ai that seeks create events and alerting without relying on audio. 



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Good day everyone. This is Ed Maguire, Insights Partner at Momenta Partners, with another episode of our Edge Podcast. Today our guest is Rick Bulotta who is one of the founders of the industrial IoT platform market, he was a founder of Lighthammer and ThingWorx, he’s a technologist and entrepreneur, and I think one of the most insightful commenters or critics of technology markets today. Rick, it’s great to have you.

Thanks Ed, pleasure to be here.


First, I’d love to get a bit of a look into your background, and what has really shaped your view of the markets in technology, and what has brought you to where you are?

Sure, obviously been a moving target. My first gig out of college was in the steel industry, working in steel plant operations, heat treating, basically armor-plate for military vehicles. But when you spent time in the plant you quickly learn that the exception is the rule, you learn how the real world works pretty quickly, I’m a few years out of school and have 15 union steelworkers reporting to me! It’s an interesting life experience.

What also worked out well was, this company was super-progressive in the way they applied technology, the company was Luke & Steel, South Eastern Pennsylvania. It was about the same time that the PC was starting to come out, and because I was the fresh out of college kid anything technology related, even in my role in steel plant operations got thrown my way. So, we invested a lot of money in automation, I really got intrigued by that, I spent the next couple of years whilst doing my day job going to our county library, signing out software, bought a PC, taught myself technology, taught myself to code, and the hook was set. The company was making big investments in its own industrial IOT organisation, a lot of remember back in the day Dec Vax stuff, BMS, RSX, all that crazy stuff.

The things we were able to accomplish then with the technology we had at our disposal were mind-blowing, we had Gooies, MES systems, complex data collection, we had lots of stuff going on then. I learned a lot during those years, also how to help justify projects, those kinds of things. Long story short, I jumped out of there and went into the systems integration world for a number of years, and that’s where I started getting more exposure to package software, how you apply building blocks from companies like [02:59], Wonderware, US Data, OSI Soft, and others. So, that became my career in everything from pet food plants, to candy plants, to automotive plants, you name it I probably spent some time on them.

That’s where I also got my first exposure to a company called Wonderware. Ken Forster and I have a history there, in fact that’s where we met, but one of the more progressive companies, not only in terms of technology, in fact I’ve heard some stats that they’re in about 50 percent of the world’s plants these days, but never the less very ahead of their time in terms of user experience, developer experience, and just as importantly the way they marketed themselves, it was a larger than life image. We used to have some fairly tongue-in-cheek ads with people in underwear, ‘This is not Wonderware’, we used to spend $1 million to $1.5 million a year on a part, when at a time we were doing $18 million in revenue, so it was a different culture, but all about creating excitement around what you had. That influenced me greatly as I went forward in my career as well.

So, I had different roles there, sales, key account sales for the North East US, technical roles, we did a lot of merger and acquisition, so I dealt with a lot of that product integration. I did three stints there, my last there was a key technology officer, but the interesting side note is, both times I left Wonderware previously, my wife was pregnant within about a month of me leaving, so I was a little bit nervous the third time I left! But dodged the bullet so to speak.

When I left Wonderware the last time, it was seeing this opportunity kind of above all of the information systems, centres and controllers that were out there in factories, utilities, and infrastructure. No one was tying those together and it seemed like a sort of a natural problem to be solve, and that’s where Lighthammer came from. So, I like to jokingly think of that as the Intranets of Things, we’re typically behind the corporate firewall. The evolution was pretty simple, and I’m a believer in this in broader IFT applications as well, it start with visibility, let’s not forget that people are still the centres, decisionmakers, and actuators in a lot of business processes, so if we can use technology to give them some kind of superpowers, the ability to see things they couldn’t see before, assimilate data from all these different places, that kind of what Lighthammer started, unified visibility to all the stuff going on in these industrial environments, and resonated super-well customers, extracted big value, and then it evolved to becoming a platform for integration with their other line of business processes, whether in the plant floor, ERP, all that kind of stuff, started to get some very large global customers leveraging our technology, got on SAP’s radar screen, and in 2005 we were acquired by SAP.

I spent the next few years in product management roles, but the coolest role I took then was actually in SAP research, so I had a very incredibly smart team in Dresden, I spent a lot of time working with them on future factory initiatives, envisioning what’s the next gen of all this stuff look like. We had an initiative called Real World Awareness, think of it like what could happen to any kind of business process if you could inform it with real data from the physical world, and if you could actuate things in the physical world to close a loop on that. So, we looked at retail, healthcare, public safety and security, manufacturing. Once again, the lightbulb went on that there’s a gap here, its too hard, people are building and having to stitch together pieces, parts, at too low a level to make it cost-effective, or broadly deployable, and that was the genesis of what became ThingWorx.

So, the basic concepts then were, let’s take all this learning we applied from very mission-critical kind of applications in the industrial environment, very heterogeneous environments where you’ve got a mixed bag of controllers, centres, systems, and soon, and also the other big takeaway from both of those was the importance of legacy in brownfield; you don’t take stuff out, so, if you’re trying to make a building smart, a factory smart, or connect to existing products, you have to consider the impact of what’s already out there and leverage that. So, that informed a lot of the architecture to boast ThingWorx, and Lighthammer.

Then, as you know, ThingWorx grew extremely rapidly from 2010 up to the end of 2013, we were just about to do our see-around, expand our global sales force, and PTC had had their own internal initiative to build an IoT platform, came down to visit with us and decided, ‘Hey, we can get a 1½ to 2 year jump-start on the market by working with ThingWorx. And the rest is history.

We became part of the PTC family, and obviously they’d been building that ThingWorx not just as a product but as a brand, some of the stuff they’d brought in around Kepware, AI, and Augmented Reality have turned it into a really fascinating platform, and I’m very proud of the legacy of what they’ve done there.

I’ve been doing start-up stuff at this point for almost 17 years, decided I needed a little bread, that’s when my wife and I bought a 155-year old house, I switched my jobs from technology to carpenter, plumber, electrician, you name it, and that was a really good project for a couple of years. Finally got that done, and there’s an opportunity vacuum, ‘What am I going to do now?’ I had plenty of side pursuits to get me in trouble. So, this is looking for something interesting to do, and I ended up doing some advisory board work for start-up, part-time engaged with Microsoft which we’ll talk about a little later. So, that’s basically what’s filling my time now, but as you can see it’s a continuum from this mission-critical, things blow up and people get hurt, the environment gets damaged if the systems don’t work, up I’m a believer in this very heterogeneous you’ve got to stitch these connected products and stuff into other business processes and data sources.

Anyway, we’re all bio-products of our past.


Absolutely. Could you talk about some of the early challenges that you faced when you were looking to instrument, and I would say modernize, or bring industrial equipment into an information era? What were some of the initial either technological or organisational or business challenges that you faced early-on? And how you were able to find solutions that ultimately would lead to be able to package some of the insights and best practices into package software?

I’ll go back to the fact that it’s sort of a continuum from connectivity, to visibility, to integration, so clearly that last foot connectivity is a must, and to your point at the time a lot of these systems were very proprietary interfaces, technically off serial connections, you name it – we encountered it. But that also I think was a seminal moment for me from a product and technology point of view, realising the importance of abstraction, abstracting away these devices, in essence what we might call digital twin today, but thinking how we abstract a way, what they are, and how you interact with them, and what that actual connectivity might be, and put an API or veneer on top of it that allows you to leverage them and weave them together in new ways. So, yeah, probably I would say that last foot of connectivity.

Security interestingly wasn’t that big an issue at the time because virtually none of these systems had any security, security was if you’re not physically plugged into it, you’re not talking to it. And I think at the time very-very few industrial environments were connected to the general internet, so that attack surface didn’t exist, so I joked earlier it was a kind of intranet of things problem.

In terms of people dynamics, I can’t think of too many exceptions to this, once people saw the benefits of expanded visibility where people in quality could see what was going on in operations, the service technicians could see the state of equipment and the electrical infrastructure. Just that aspect of it, people were bought in, they got it. I remember advanced manufacturing research whose now part of Gardner, issues a report, I’m going to guess probably 2003-2004, but the space that we created was called Enterprise Manufacturing Intelligence, they wrote this piece that said, ‘This is one of the rare no-brainer investments’, and they’d spoken with a lot of companies that again just that first wave of visibility and people collaborating together to solve problems had a massive ROI. So, it’s kind of like the low-hanging fruit situation, a lot of value just from that first step.

So, I would say the cultural challenges at the time were fairly minimal.


How did you translate that to really a much broader platform when Lighthammer became part of SAP? SAP has a really broad reach, and of course they have this expertise in business process re-engineering, and back office, but was there a need to adapt the messaging or go to market approach that you’d had as a start-up, once you were inside SAP? And how did you manage to propagate the value through a large organisation like SAP?

Great question, and you know, it’s interesting; think about most enterprise software companies, every year they roll out a number of products and offerings, they acquire products and offerings, and you’re not just in a battle for mindshare of the customer, you’re in a battle for mindshare of the sales force, your own internal sales force, everything goes through a fashion phase. Manufacturing was very hot, the first year, I forget the exact number, it was like a 7-10x bump in revenues, and we were really hitting our stride at Lighthammer. What got their attention, and the sales forces attention was the multiplier effect. Let me elaborate on that a little bit.

If you think about most companies, they’ve got somewhere between four and ten blue collar workers for every white collar or back office worker. Those are typically very underserving in terms of software, obviously licence revenue, but different solutions were needed, very different experiences, different functionality, also the processes that those people performed on a day-to-day basis were way-way more invariable than purchasing, accounting and so-on. So, it required a sales team that was capable of selling more of a solution sell, as opposed to, ‘Hey, this is the best procurement software you can get’. I work with a lot of companies even nowadays that realise when it’s that type of a sell you need specialist sales people; long story short, we took the best of our go-to market organisation at Lighthammer, the amplifier effect, the size, the reach, and the manufacturing presence of SAP, and really got it done. I mean, you’d have to ask the SAP folks what their perspective is, but I would argue it’s probably been one of the more successful acquisitions in terms of return on what they paid for, and invested in the company, and it’s still much to my surprise still a very viable product today.

Obviously, a company like SAP, we invested in very important things that a small company might not, around localization, accessibility, going after a global market, but for the most part it was that amplifier effect than a vacuum of underserved demand and need.


Expanding on that, as you looked at the idea behind ThingWorx, what was the whitespace that inspired you to go out and start a company again, after you’d created a business that was so successfully integrated into one of the top global software companies in the world? What were they missing and what did you see as the new opportunity that gave birth to the genesis of a new company?

What’s also interesting is, it wasn’t for lack of trying to get it started within the umbrella of a large organisation, but it’s just fundamentally difficult for many companies to organically… innovate is not the right word, they’re an extremely innovative company, but that sort of start-up, it’s a different model of everything, from how you develop, how you deploy. Long story short, we gave it a go and explored different ways to entrepreneur it, and it became clear that wasn’t a likely outcome, so logistically, let’s get the band back together, the partners I had at Lighthammer, I brought some new team members in, but the fundamental gap was the same, it was just too hard for people to build applications.

If you think of ThingWorx, a lot of people thought of this as a top-to-bottom IoT platform, which we were and we had those capabilities, but ultimately at least in my perspective, the primary value we were creating was building that application on top of this very-very heterogenous blend of stuff, and enabled me to do stuff 10x faster, that was always the goal; how can we reduce friction of deploying this stuff? All the pieces and parts were evolving, they were there, the technology components weren’t really the issue, but it’s how you put them all together in a cost-effective way to do something useful.

An interesting spin on that too is, one of my mentors and a guy I respect greatly when I was at Wonderware, a guy named Phil Huber was instrumental in that whole design experience, how to develop or build applications there, influenced me greatly. When we started ThingWorx we needed to grow our team, and I was lucky enough to have a wrinkle in time where he and a couple of very talented people were available in Southern California, and basically was allowed to leverage their experience in building that developer experience, add them to the team, and just absolutely critical to how ThingWorx evolved. So, it was the ability to cherry-pick the very best in the industry that’s hard to do organically in a big company, but also I’ll be honest with you, it’s easier the second time, you know the pitfalls, fundraising is easier, so a lot of those aspects, it was just a matter of identifying the gap… and this is our driving mantra… how do we make it 10x easier and cheaper, and how do we make the easy stuff easy, and the hard stuff possible? That was basically the mantra for the business.


That’s dovetails nicely into the concept of the massive transformational purpose, or the exponential impact when you are talking about a really disruptive approach, which I wouldn’t necessarily categorize an IoT platform as being disruptive, but in a sense of being able to unlock value that essentially was untapped in so many of these organisations with critical capital assets. You had applied a fairly innovative approach.

Can you talk about driving business value from the enabling technology? I think a lot of people understand the waves of evolution that have benefitted innovation, whether it be the falling costs of processing and storage, and increased connectivity, cloud computing of course; how did you go about deciding on, and defining the business problems that you were going to solve, and proving that out so that you could see it could become a real platform model that would give rise to replicable solutions?

Good question, so two dimensions to that, one if from a value creation perspective, and also combined with the go-to market approach was that if you’ve just invented the flying car, or the flux capacitor, and you’re going out there and try to sell it, you’re in an evangelical mode, no-one has budget for that, no-one fully understand what its business impact is going to be. So, we have this concept we call bridge functionality. Bridge functionality is, what are people used to buying, or at least have some awareness of that’s a component of what we do that we can get in there, set the hook, deliver value, and then convince them they also have the flying car, and the advanced functionality waiting for them when they’re ready. That pattern worked at Lighthammer with remote visibility, and then in the ThingWorx world it was the same kind of thing, multi-system visibility interaction, so kind of like, ‘Hey, I get it. This is sort of a specialist kind of BI solution’, it turned out to be obviously much-much more. So first, what are used to buying, where can you get low hanging value? It came down again to visibility and integration.

Similarly, I’m kind of… cynic-sceptic’s not the right word, but I don’t really think there is such a thing as the IoT per se, and by that, I mean it’s just one set of capabilities this end connectivity, and edge intelligence, that we have at our disposal now. But the companies are really doing things of value, its deeply integrated into their other business processes, into their customers, partners, and suppliers. I get the consumer highly linear connector, connector sensor, very simple apps, I’m not sure that’s an area where companies like mine delivered a lot of value, but if you fast-forward a few years, now companies are looking to do a lot of the basic blocking and tackling, device-management, massive data ingest, secure connectivity and provisioning; that’s become the purvey of the big cloud vendors, which isn’t surprising to me.

So, again the focus on the application tier, and the uniqueness that each and every company had, my contention is that no two applications are the same, even a company that builds a fleet tracking app, or a remote service or remote management app, there’s always a level of customization that’s needed into their other processes and data-sources, or interacting with other parts of their value chain. And so, this tooling-based approach, we did have to evangelize that a little bit early, but I think to your point also is, and I advise all start-ups to do the same, is work intimately and closely with your first customers to help them along this journey.

But the quid pro-quo for that is ask that customer to share what it’s done for them, because when you’re early in a company’s life those success stories, the value stories, and concrete ROI are gold, they’re worth more than any money you can raise from venture capitalists. So, that aspect too, collaboratively learning, iterating, refining you story. The truth is, your customers are going to tell you what your value prop is, you can have some ideas and you think what it’s going to be, but it’s that first 10 or 15 customers that help you clarify that vision.


I’d like to turn the focus to operating within hype cycles. I think when ThingWorx came on the scene it was just about the time that the term IoT hit the public consciousness, and you saw a number of large companies go to market, rebrand their strategies, and put I would say the forecasts of devices, billions of devices in the world were hitting; essentially this classic Gartner-hype cycle came into play, and over the past several years we’ve seen a bit of… not true disillusionment, but certainly initial growth expectations had to be tempered because of the nature of hype. I would love to get your perspective in navigating expectations and execution throughout the early stages of a hype cycle. How do you orient a business so that it remains on a firm foundation throughout what can be a lot of misperceptions, or disconnects, in the public perception?

Sure, there’s a couple, one is I always felt like I should have sent Amazon gift cards to the CMOs at IBM, Cisco, and others, they basically did our advertising for us, created massive awareness and demanded the internet… they all had different names for it, but at least it got it in the collective consciousness earlier than we ever could have. Evangelical work is hard, its expensive, it’s difficult, so the fact that a lot of larger companies were doing that, and the reality of their offerings lagged behind left a massive opportunity for us.

Second, you had to deliver on that. I go back to this fact that I would say as a company we viewed it as just a continuum, it was a continuum from all, just as we did at Lighthammer was a continuum from what we did in industrial automation, Human-Machine interface, and Skater. What we did at ThingWorx was a continuum of that for that class of problems, and a new class of problems, so we never really viewed it as this massive discontinuity, and in our conversations with customers we focused on very clear ways they could apply it, get value and so-on, rather than ‘This is going to change your world forever!’ and it can, it’s an empowering tool for the companies that are true innovators.

But innovation, this is again one of these white blessings I’ve learnt; I’ve sat in so many of these vendor-awards, you go to industry events and shows, and a vendor and a customer get on stage and talk about how awesome it was, how much benefit they got. When you kind of butt-hole the customer afterwards, pull them aside and ask them a few questions, you find out that the real innovative things that they did were not typically in that vendors platform, they were around it, they were the things that they envisioned, and they created whether they’re new processes, new technologies, stitching stuff together, that light-bulb went off for me early that you have to empower your customers to innovate, ‘Here’s the magic beans’, and you water them and innovation will happen, its empowering their teams to look at problems, look at opportunities and new ways, so that technology and application development was not the friction point. So, that was at least how we viewed it from that perspective.


I would also just make the observation that in developing a platform, you’re creating this sub-foundation that enables that innovation, you’re not forcing business process or established best process, particularly in a market that’s just starting to evolve in terms of what we would call industrial IoT; it’s one thing to automate payroll or HR, but in these emerging markets it’s a very different animal. As you’ve watched the industry evolve over the past few years, is there anything that has surprised you in terms of how your initial vision of ThingWorx has evolved and developed, and certainly with the rest of the market giving rise to hundreds of, I would say ‘platforms’, that you had a lot of companies that were approaching the problem by trying to become platforms rather than applications. How do you view the state of the market now, versus your original view? And ultimately, we’d love to get your thoughts on the IoT platform market.

My business partner, Russ Fadel can confirm this statement, but I remember meeting with Zia Yusuf who I knew from SAP days, he’s with DCG now but he was CEO of a company called Streetline, doing in-street parking sensors, you can find open spots, real application of IoT technology. Long story – short, all our collateral and our stuff, talked about what an awesome platform we had, he just sort of chuckled and said, ‘You’re not a platform when you say you’re a platform, it’s when customers define that you are in fact a platform, and the community, and the eco-system building around you’, and that stuck with us, the importance of building that kind of eco-system play as well, that the Lego blocks that customers had to build from needed to be not just from us, pre-integrated with all this other stuff.

But those dynamics definitely affected us quite a bit, and understanding what is a platform, and the importance going back to this heterogeneity, accepting that, that’s just the way of the world, and you have to be able to accommodate that from a platform perspective. But I would claim that in IoT today there really is no such thing as a single IoT platform; we’ve got platforms for Edge, we’ve got platforms that are optimized for device-management, data graphs, things like that. We’ve got platforms for AI and analytics in the IoT stage, we’ve got platforms that are built at the application tier, building the actual applications and rules, and visualization. Those are all very different disciplines, very different architectures, very different needs.

I almost think it’s great that they’re all iterating independently, unfortunately it does put some return to the customer some effort to tie those together, but you can see eco-system forming around the bigger cloud vendors, around platform companies like PTC and so-on, but ultimately it’s that there are many types of platforms for the IoT and its somewhat used-case specific, knowing which ones you need to select and focus on, and leverage together. In fact, I had numerous customers that had multiple IoT platforms, in many cases inclusive of their own, some of the world’s largest companies have built their own IoT platform that have millions, if not tens of millions of devices connected; you don’t talk about that as an industry much, but they’re out there. And whilst they wanted to move to more commercial products, you just don’t retrofit 10,000 medical devices, it doesn’t happen.

So, long story – short, it was just rethinking this tiering of platforms and what functionality needed to be provided at each level, and how you needed meta-platforms. One thing I’m very proud of with ThingWorx is that it was designed from the get-go to sit on top of other people’s device management, device connectivity, and data ingress platforms. Whilst again, we had the need and we had a very awesome offering top to bottom, we recognise the customers have this mixed bag of stuff that we need to accommodate to solve their problems. So, that idea that this meta-platform sitting on top of other platforms I always thought was one of the key value props of what we built.


If you turn the focus to the rapid evolution of AI and machine-learning, how does that impact the potential power and application of these technologies, these connected technologies going forward? What’s your sense on whether expectations may be aligned to reality, and some of the potential ahead?

I think we as an industry and certainly the trade press tends to lump AI and ML, and all that stuff into one big bucket, in reality I kind of break it up into multiples or have their own unique value. So, we think of AI and ML as techniques for new modalities for interaction, classy examples are Voice Agent, Alexa, Cortana, Siri, things like that, so leveraging AI to find new ways to interact with things. Second is one that I find very-very exciting, is what I call medisensing and that’s using audio, imagery, other sources of input as medisensors, applying AI in NL algorithms to turn them into some other insight, traffic patterns, foot traffic, thermal analysis of a part coming out of a piece of equipment [from 36:37 to 36:41, blank audio] coming out of a paint booth, all these kinds of things, seeing some fascinating stuff with audio as well, it’s just catching on.

There’s an interesting company with a deaf founder, a product called Wave IL that he recognised voice is interesting, but if you’re hearing-impaired how valuable is to know that a smoke alarm is going off, or someone’s knocking on the door, or a baby’s crying, or the water’s still running; so, they built some clever technology to basically do sound synthesis and turned that into a meaningful event. We’ve seen a lot with imagery, with drones, with fixed cameras, with cameras in public spaces, I think we’re just at the start of that, democratizing that, making that easier is a massive opportunity.

Another one is just anomaly detection, we see a lot of work under way to characterise how equipment devices operate, and processes operate normally, and then use those patterns to help us detect when something isn’t right. A little side note there, I think the obsession is perhaps too much on the devices and assets, and not enough on the processes. It’s interesting, a lot of the same tools we have can be applied to the data from the processes, not from the equipment, so they may span multiple pieces of equipment, people and so-on, that to me a big growth area. And then just applying machine learning in AI for that kind of off-line insight generation, you’ve seen patterns in corelated data in event either for sheer size of the data, inability to bring those data steams together if humans weren’t able to do so.

So broadly, I’ve probably missed something, but I do chunk it up into a bunch of different areas that can all evolve independently.


That’s a helpful way of looking at this range of technologies, and I haven’t heard it expressed that way, it maps very logically to some of the value props. I just wanted to turn the topic to another emerging technology, which you’ve been pretty vocal on, which is blockchain! I know you’ve been vocally and quite correctly skeptical of the enormous hype, I’d love to get your assessment and your view of what happened, what’s real, where have people missed the boat, and what is actually real that you think may come out of a lot of this innovation?

I know I have a cynical outlook, I would like to say I’m bullish in the long-term, and puckish in the short-term! It sickens me sometime how great opportunities in a lot of technologies just gets so over-hyped, and the customer expectations can never be met. It can be counterproductive when too much money blows into a space too early. Hell, I would make the argument we saw a little bit of that with IoT 1.0. Remember, RFIB was going to be on everything.


Absolutely, that’s a great example.

What’s funny is, I used to joke it’s a rare mean reboot, IoT now means something very different than when Kevin Ashton coined it, but, nevertheless. Blockchain, the idea of multiparty data ownership, no single party owns it, immutable record keeping, appropriate levels of security, encryption, and data sharing across the value chain. Those are all massively valuable things, and I think too many people conflate crypto-currencies with some of the other applications for blockchain, we’re already seeing that. The technology requirements are so dramatically different, proof of work kind of things and energy demands that crypto could never apply in an IoT scenario. So, we’re already seeing different technologies being created to address some of those issues.

I also am skeptical about the replicated nature of a blockchain being the devices are going to play a role, but I just don’t see them as the heavyweight active nodes on the network. We also see a lot of the used cases and early pilots where all of the nodes in the blockchain are all in the same vendors cloud, and owned by the same company, to me that kind of defeats the multi-party data ownership problem, potentially. We’ll see how that evolves.

The other things are, at its core there’s so many interesting things, you read the books and the literature that say, ‘Oh, this will be integral in managing your healthcare record’, well, I agree there’s potential there, but today’s blockchain implementations are not designed to store an MRI, or any kind of rich data. There’s packs and early implementation, underlying a lot of the implementations its very limited in the way you can query them, the way you can manage granular permission, so I think there’s a great-great opportunity in the spirit of what we talk about here, again this common almost a throwback to the old… remember the buzz exchanges.


Oh yeah, the trading exchanges, the Ariba and Commerce one, and all that, yeah.

It’s kind of a throwback to that maybe with some new and more modern… crypto’s got its own, like cryptocurrencies, to me that’s a different space, but nevertheless I do think we’re going to see some exciting innovation, it’s going to take time and we’re going to have to start, maybe step back and look at the problems people are trying to solve, and design the technologies to do that. And not pretend if the right tool for the job is a blockchain ledger with references to a traditional datastore, or a blog datastore, whatever, great, and there’s some architectural work in those areas; but it’s this silver bullet magic beans kind of mindset, as you know I have just a visceral response to, nevertheless, I really am bullish of the overarching concepts and benefits. I think that’s important.

I’ve been talking about end-to-end what I call extended PLM, cradle to grave view of everything about a product from the day the parts were procured, and made, to how it was built, how it was distributed, serviced, used, and the ability to share that across a value chain is massively valuable. Unfortunately, value chains are becoming even more and more complex, it’s not uncommon for the brand owner of the product not to be the one that designed it, not the one that built it, not the one that shipped it, not the one that serviced it. So, this whole idea of multi-party data sharing and data commerce represents I think one of the next big spaces, it’s an area I’ve looked at a few times, whether blockchain and its iterations solve that problem for us, I’m hopeful, but that whole space… and it’s not just data commerce, it’s almost like an API commerce, but anyway!

At the same time let’s just be pragmatic, blockchain, autonomous vehicles, all exciting technologies that could be super-transformational, let’s just be pragmatic in how we spin them, and when we tell customers they’re ready for broad adoption.


Well, that’s so critical is managing expectations. The big challenge of course with technologies that get over-hyped is, you get this massive influx of capital, and we saw that. When I first started on Wall Street one of the first things that I was involved in was writing initiation reports on Ariba and Commerce One, Cybal, and i2, and one of the things we were doing was applying a traditional discount of cash-flow analysis to these companies, to try to justify some upside of the stock where they were trading, and this was early-2000. Of course, they were trading at ridiculous valuations, and people were using measures like comparable multiples of revenue, so your classic ‘Well, my dog’s worth $1 million because I traded it for two half-million-dollar cats’. When you run these discounted cash valuations, you have to actually get to a $40 billion run-raid in 10-years for Ariba, to justify where it was trading at 10 years earlier.

Of course, Ariba survived and its now a very critical part of SAPs echo system, but nowhere near what people thought, and of course it always takes a lot longer for visions to become reality. I’m very much with you there, and of course we’re seeing the internet bubble 2.0 as it played out in crypto is unfolding in about a third of the time, or even a quarter of the time! So, we’re cleaning things out a lot more quickly to get to the real foundation.

It’s funny, a little side anecdote. My first home purchasing experience had to be delayed about five years because of investing an i2 on margin! So, lesson learned, right!


Ohhhhh! I feel the pain!

Again, one of the takeaways, do your homework. I like to inform my opinions and actions on data, its increasingly difficult to separate good data from bad data, but that’s a lesson learned from that experience.


Let’s talk a little bit about the move to a big company, you’ve been an entrepreneur and worked in a lot of different types of companies, but talk a little a bit about what had attracted you to work with Microsoft?

Obviously, an all-in mindset from top to bottom, Sacha, Bill Gates, really see the value of this connectivity and how it can transform just about everything in our lives. A very and vocal verbal commitment to investment over the next few years, and quite frankly because of my background in industrial automation, and the uniquity of Microsoft in that space, I’ve always appreciated the market leverage, power, and potential that Microsoft had in this space. So, as I said, I had this opportunity vacuum, reached out to Sam George who runs the Azure IoT team, and he graciously offered me an opportunity to help them with their strategies. So, I started [inaudible 48:31], occasionally, unbelievably brilliant team, really some of the brightest people I’ve worked with. But they’re an entrepreneurial business inside of Microsoft, there’s a lot of aspects to the way we run that group that are very entrepreneurial.

So, it’s kind of the best of both worlds, the reach and leverage, and resources of a big co, with the agility, let’s be creative, lets focus on our customers, that’s the part that gets me up every day is when customers do something awesome, that’s totally my energy source. Very engaged with customers, it’s an exciting time and its one of the things I do, I do a couple of days a week for that, and then working with a handful of start-ups in and around emerging technologies, robotics, AI, things like that.


That’s great. Sam George was a prior guest on the podcast and he’s a truly impressive guy, an incredibly eloquent advocate of connectivity and value from connected technologies.

And he’s built an extremely impressive team across the board. Stay tuned, exciting things to come.


Looking forward to it. Looking forward, what are you most optimistic about, and what are some of the concerns that keep you up at night, as the market and the world are unfolding over the next several years?

Primarily in and around with the IoT.


We’ll start there, but if you want to go more broadly, I think that’s relevant too because everything’s connected.

I think we’ve covered a lot of the challenges that are, can we still get another 5 to 10 x easy button? Is there some transformational… I still think it’s too hard to build applications, our building blocks have gotten better, cheaper, faster, richer. I still think there’s a step-change improvement in how we build applications, and I think we forget just like we talk about applications at AI – we talk about applications in the IoT; there are analytics, there are human interaction, there are process integration and rules, there’s all kinds of stuff, and there’s developer-oriented stuff versus casual user. So, transforming how people can continue to add value to all this stuff we put in place, I think the tooling area is super-important. Democratizing AI and ML is a big problem, it’s still too many propellers and heads required, too intense.

Some of its unavoidable, data prepped is grunt work, there’s some stuff that we can do better, but democratizing all those AI and ML technologies I think is a big opportunity. New modalities for interaction, I applaud what Jim in PTC have been evangelizing with the AR, the mixed reality experience, maybe it would be hard to guess what the adoption rate’s going to be, but I think there’s every element of that from the devices themselves, to the tools we use to build applications are getting better and better. So, hopefully we’ll see some mainstreaming of that soon, and all of the other pieces we talked about, like just the hype disconnect, I’m just hoping there’s a return to sanity at some point.

I do think also we’re going to have a privacy backlash in the not too distant future, we’re already seeing bits of that in the social media world, but I don’t know that with all of the IoT sensors, cameras, things like that, or even in complex value chains; you may have seen some of the backlash in the Ag community about who owns the data from farms, from seeds, from whatever. So, that data privacy, data sharing, those I think are going to be some interesting challenges as we move forward. But overall like I said, I see IoT as this other new awesome tool in our tool-box, and for me the optimistic point of view is there are so many bright people that if tools were not their limitation, could do amazing things. That’s always been part of what I tried to help do is, how can we democratize app creation so that more people can take their ideas, and make them real? Even just make them pilots or whatever, that’s valuable as well, fail fast/succeed fast.

I do believe we’re going to see some progress there, and we need to de-geek some of these technologies, more and more and more.


Absolutely, technology – one of my theses is that over time they become more transparent, as they become easier to use. But that’s an evolutionary characteristic I think, of all technologies.

Are there any interesting smaller companies, or emerging technologies that you’re keeping your eye on?

Yeah, I won’t put plugs in specifically for some of the companies I work with, but some really innovative stuff. I guess I already did, well, I have no fiduciary involvement with wavier, I wish I did, I probably should. But that medisensing area is really exciting to me, a company I’m working with does a little bit of that in the drone space, but it can be more broadly applied to any robotic scenario, that’s very exciting. Simplifying that last foot of connectivity, a company I work with in that space I’m very excited about. I think there’s a company I work with that I believe hasn’t actually delivered on the claims of making AI and ML in industrial processes easy. I believe they’ve done it and they’ve shown some real promise with their early customers, being there a week or two weeks and have amazing insights coming out. It’s hard, it’s really hard to do, so that’s a scenario where I think we’re going to see increased democratization.

Other, maybe not small company stuff, I’m excited about the potential of 5G, not for any of the reasons that we would have said two or three years ago, it’s nothing to do with bandwidth and things like that, but there’s some really interesting stuff that I think 5G’s going to transform both industrial IoT, and the broader IoT, so definitely keeping an eye on that.


That’s great. This has been an amazing conversation Rick, I always like to round out my podcasts with a request for a recommendation that you might provide to a colleague or friend, and I wonder if you have anything you could share on that front, anything that you would recommend?

Two radically different ones, but they’re kid of my go-to. One is a book from Jeff Hawkins, I had the pleasure of meeting Jeff, he was the founder of Palm Computing of course. His real passion was neuroscience, so through the Redwood Neuroscience Institute they formed a company called Momenta, but he wrote a book called ‘On Intelligence’, which I think is kind of a must read if you want to understand how the brain works, and Numenta’s doing some really interesting stuff in hierarchal temporal memory, for a different way on how we can digitize how the brain works. I really believe we’re taking a lot of the wrong approaches today, very digital approaches to an analogue and chemical problem, a fuzzy problem. So, that’s a good read.

At the completely other end of the spectrum, my wife turned me onto a book that I really enjoyed called ‘The Book of Joy’, and it’s just a fascinating blend of the Dalai Lama, and Reverend Tutu, getting together and talking about joy and happiness, and what can help get you through some of our day-to-day challenges, highly recommended, entertaining read, and hopefully everybody will get some insights out of it.


That’s a great recommendation, and of course happiness is a known performance enhancer. Shawn Anchor wrote the book, ‘The Happiness Advantage’, which has been recommended to me by a couple of folks too. Those are great recommendations. Rick, it’s been a pleasure learning so much about your background, experience, and insights, and again.

This has been Ed Maguire, Insights Partner, at Momenta Partners, and our conversation has been with Rick Bulotta. Rick thank you once again for taking the time to speak with us.

My pleasure Ed.

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