Podcast #136 The Corporate Spin-Out

Good day and welcome edition 136 of our Digital Industry Leadership Series. Today I’d like to welcome Matt Kirchner, Chief Product Officer for Atonix Digital, helping companies simplify asset performance management. Matt leads the product management and customer success teams at Atonix, bringing nearly two decades of experience, reliability and performance consultant and product manager, and training as a mechanical engineer to solve the operational challenges of its clients. Before the spin-out of Atonix and Black & Veatch Matt served as product manager for their ASSET360 product line as well as the supervisor for their 24-hour a day monitoring diagnostic center. Matt welcome to our Digital Industry Leadership Podcast.

1:20

Yeah, thanks, Ken. I enjoy the show, and happy to be a part of it.

1:23

And really happy to have you on here as well. So, let’s start a little bit with your own professional leadership journey, what would you consider to be the common threads of that leadership journey?

1:37

I think that’s an interesting question, I’ve heard you ask other guests that question and I’ve pondered it myself. From my personal career I think it’s been more of a steady progression more so than a big jump from here to there, and so I kind of think of the common thread as continuous innovation, how do we keep getting better. When I first started, we were just beginning to offer some remote consulting services for at the time mostly power generation plants. Fairly simplistic we would pull in some data a couple of times a week and run some spreadsheet tools and offer some advice. Then it was always just, how do we do this a little better? How do we use a little better math? How do we do this more frequently? And then ultimately go into a real-time solution in about 2009.

Then really recognizing that software that we’re using to facilitate a service has its own inherent value, how do we now commercialize it as software, and that once you have the software up and running how do you make it better and really start solving the problems more efficiently? So that steady progression it’s just incremental innovation – how do we do things better tomorrow than how we’re doing them now?

3:14

You know, it’s interesting you say, ‘No major shifts’ yet I see you coming out with a mechanical engineering degree, and then jumping into your first role with Black & Veatch of course, a major construction company at the time, but as a software implementation engineer; so, what inspired your no so major shift jump! To software into Black & Veatch?

3:37

Yeah, good point, good catch there. I certainly didn’t set out to be in software, I think it was just opportunistic that I landed here, and frankly when I was talking to the hiring manager at the time the thing that really intrigued me was maybe a couple of things; he would describe how the team at the time was focused on leveraging thermodynamics, and really focusing on plant efficiency and how do you operate more efficiently. He said, even if we save our customers just a fractional percent on their efficiency it saves them millions of dollars, and so frankly I think the two things that attracted me were a) that it was a real problem, it was a real benefit to the customers, and b) it was actually applying things that I had learned in school. So, I think those are the two things that attract me to the position, and it just so happened that software was the vehicle that helped me apply that.

4:43

We’ve had many guests on this program who have had actually similar trajectories, in some cases, we’ll call it a full-stack engineering experience if you will, and many actually starting off literally at the chip level. But it’s interesting, I was tongue in cheek earlier about the shift because I do believe there is a steady progression in that regard of moving that direction, and software amplifying kind of the mechanical engineering skills, especially when you’re talking about asset performance management or larger OEM equipment. Something you said a moment ago about the hiring manager at the time, I believe it was Beth Comstock over at GE when she was Chief Marketing Officer, who came up with this concept at GE Digital of the power of what they used to call one in two percent, and how dramatic the savings could be simply saving one percent of the fuel cost for a diesel locomotive as an example.

5:42

Right yeah, definitely.

5:43

And that was brilliant, that was absolutely brilliant. And digital industry and GE in particular really come back to that, it’s simply, 1) how do we make things more efficient, but then 2) how do we transform how we can interact with things later on. So, we’re already off to a good start because I think we’re at least aligned on that.

6:06

Yeah, well one thing I think is interesting is, even in our space many times customers are trying to prevent that one big problem, but what they end up finding is it’s the aggregation of many problems that drive the savings, more so than just the one major catastrophe.

6:27

Your progress through increasing leadership roles and monitoring diagnostic, as well as operating intelligence, what problem at the time were you trying to solve, and for whom?

6:44

When I think of that term, operational intelligence, and what we hear from customers, it's usually two related issues that they’re trying to solve. The main one is we have more equipment failures than we can take, those equipment failures are costing us a lot of money, downtime, and maintenance. And maybe second or parallel to that is we have a whole bunch of data, we have all this operating data that just kind of sits there, and we don’t have any way to do anything pro-active with it. So, when I think of the problems that we’ve been trying to solve for folks, it’s how do we leverage all that data to prevent those equipment failures? And frankly, that happens across many different industries.

I mentioned earlier that we kind of came out of the power generation industry, but what we found is the same problems exist whether you’re thinking of power generation, or oil and gas, or pulp and paper, chemical processing, or water and wastewater, but basically any large industrial or manufacturing environment they’re all saying, ‘I have a lot of data and I don’t want things to break.’ And so those folks usually have people in many different roles that share in that problem, so sometimes it's engineering, sometimes it’s the maintenance team, sometimes the operation team, management, everybody has this shared vested interest in solving the problem by keeping their plants up and running and running efficiently.

8:25

As we said earlier, you were the product manager for the ASSET360 product line at Black & Veatch there, and I know a lot of what you had just discussed really was built into that platform, the operating intelligence and monitoring diagnostics, etc. especially around process; what were some of the key use cases for ASSET360 during that time?

8:50

I think that the main use case and the main thing that people were seeking is that reliability issue, making sure the plants are running reliably, don’t let equipment fail. And so the whole idea of leveraging the platform to detect, diagnose and resolve issues, kind of that full life cycle and making sure you’re getting from that data to the action. I think what they often find is that even though reliability might have been the key use case they were chasing, it quickly shows that operational efficiency, and how we’re running efficiently to not consume as much fuel, or chemicals, or power, whatever your consumable might be, that efficiency becomes a pretty valuable use case as well.

And then frankly, if you’re preventing equipment failures it has a health and safety component to it also, you want to keep your workforce safe, and preventing some of these significant equipment failures becomes another use case that folks both GIS on.

10:08

You know what, what intrigued me about some of our early conversations and part of the reason for featuring you on this was, 1) you’ve been working on this since 2009, this is clearly a hot space in your asset performance management, and to do so under Black & Veatch was an incredible platform because I imagine the wet breadth of use cases you were able to work with. The other facet was the fact that you guys spun this out of Black & Veatch which I’ve always enjoyed the corporate spin-out models and stories that go with that. I know in 2017 you and several of the ASSET360 team spun this out to create Atonix Digital, so what was the reason for the spinout?

10:54

The timeline actually starts long ago and before I started there. There is a small team of people in Black & Veatch working on plant reliability and efficiency software, all the way back into the 1980s. I joined in the early 2000s and we kind of still had a kind of niche team that was developing commercial software, but it wasn’t as near aggressive as a traditional software company would be.

As we got to that 2009 time period and started to do this in realtime that’s where the wheel started turning, frankly, it was 2012 when there was the bigger shift, and that’s when we said we’re going to move this to a cloud-based commercial software offering, it requires investment to get that up and running, and so Black & Veatch took on that role as an investor to build the ASSET360 platform in the cloud.

So 2012 to 2017 was where the initial spinout happened, we were embedded as part of some service business lines in Black & Veatch and there are some really good complementary services to the software, so Black and Veatch was both commercial, I think software and services throughout that time period, and it worked well, but naturally you can imagine being embedded in a services P&L is challenging from a software business model. The services P&L they’re reporting on their profit, they’re trying to be as profitable as possible, and an early-stage software initiative takes a lot of investment. So those two, the whole investment business model and the services P&L were somewhat in tension with each other.

So that’s what led to the initial spinout in 2017, is just that idea of this is a separate enough business that it should be operated as a separate business and operated as a software company. So, that 2017 time period we formed Atonix Digital as at that time a wholly-owned subsidiary of Black & Veatch and began operating independently. We still had, and today we still do have, great partner relationships with Black & Veatch, so those services P&Ls that we used to be in business with, or in the same shared business, they’re now operating as services partners and resellers of Atonix software. So, we kind of operated in that initial spinout method for three years, and then actually the beginning of this year – in 2021 we made one more move because there was still a little bit of that same challenge that we had all along the way.

So even though we were outside of a services P&L, Black & Veatch as a corporation is still focused on the services business model. They actually have this mantra that goes back to one of the founders in N.T it’s, ‘Get work, do work, make money' and that totally makes sense as a services business, you sell a job, you execute the job, and you get paid for the job. But a software company or any products company really is different, you’re investing upfront to build something that you commercialize later, and you make your money on the back, instead of knowing exactly where that’s coming from.

So, we still had a little bit of that tension with inside even as a wholly-owned subsidiary, and as we were looking into our 2021 plans and talking with Black & Veatch in terms of, ‘What do we think is best for Atonix?’ and we were saying, ‘We have some great opportunities in front of us, we think we should invest significantly this year to keep pushing forward,’ and Black & Veatch saying, ‘What’s best for us? Well, we really love the services business,’ and we said, ‘You know what? There is no shortage of companies that love to invest…’ or, ‘… there’s no shortage of investment funds for software companies that are growing quickly. So, if that’s not your business model, let’s actually carve this completely out.’

So, I and three others from the leadership team executed a management buy-out and secured external funding to make sure that this thing continues to grow, and that allowed Black & Veatch to focus on what they love in the services business where we’re still partners and allowed us to push to be nimbler and quick-moving as a fully independent company now.

16:17

Well done. We actually did a much smaller version I’m sure, of the same carving out a Swiss digital start-up from a service company in Germany earlier this year. We actually set it up as a leveraged buy-out, and so yeah, you learn a heck of a lot going to that, it’s I think our third one that we’ve done, but usually, they’re smaller companies.

It’s interesting, these digital assets in some sense will emerge from a services business, typically because they’re trying to build a replicable infrastructure, or conversely, a lot of our digital investments we do on the venture side actually get a start doing a lot of services business, non-recurring engineering if you will, to drum up business, to learn, etc. And sooner or later inevitably they split that part of the business off and only focus on the digital side, typically our own net line of recurring revenue versus non-recurring, so it’s an assumed model.

Tell us a bit about Atonix Digital then, and some of your wins.

17:25

What’s been great with Atonix here lately is, ever since I suppose that initial 2017 it’s been certainly a learning process, but some of the things that we’ve learned that our core focus areas for ourselves are, the first one is how do we make complex math, complex analytics, easy to consume for the people who understand the assets? So, in a traditional model a lot of times you have a data scientist who understands the math, trying to team up with an engineering team or an operations team who understands the asset, and so just as a little less efficient, so one thing we focus on is how do we make the maths still sophisticated but easy to use so that you can just let those asset folks use it.

And then another focus area that we have is, make sure that we recognize that the math or the analytics are really just a starting point. The value delivered isn’t in the math, the value delivered is in the action that’s taken because of the math, so we want to focus on driving that process. So those are a couple of focus areas of Atonix is making that math easy to consume and making sure that the math drives a process.

From a win perspective, I consider a win just in our industry expansion journey and seeing how we’ve been able to apply our software into new industries. We have over 250 plants that are actively monitored by our software right now, and our customers and partners have resolved 30,000 issues. So, I really think those are some things that make me proud and excited about where we’ve been.

19:21

And I could understand why it might not have been too difficult to find investors for your business because if you share those kinds of metrics and you show quarter over quarter growth toward increasing those, I imagine you had to beat off most of the investors in one form or another!

19:39

Yeah, there are certainly people who are interested, and it’s interesting when even some of these shifts in business, people come knocking on your door for sure.

19:50

Yes, I can imagine, especially if you’ve got latent data which in and of itself becomes a great way to benchmark companies and build up a knowledge base of the industry. So I know investors, particularly PE firms have that as a thesis of what types of companies they are looking for, like as an example OSI PI which of course finally was acquired by AVEVA, but that one was always the benchmark conversation with PE firms talking about companies that have accrued a lot of data, right!

20:22

Well, that’s really interesting, and frankly, it’s something we’re aspiring to capitalize on later this year is, how do we leverage those 30,000 issues for the benefit of our customers? There’s a lot of knowledge that was gained in documenting how those issues were resolved. So that is something we want to put some focus area too.

20:46

Yeah. Well, look you’ve been at the forefront of asset performance management, or APM as I’ll call it going forward in the conversation, for the better part of a decade. Tell me about what you’ve seen as the largest change in asset performance management over that time?

21:06

I ponder this a little bit, but I think one of the biggest changes, and this is probably not unique to asset performance management, but it’s the idea of cloud adoption. I look back and in our timeline that we’ve talked about here, 2011-2012 is when we first moved to a cloud offering, And at that time a lot of the customers that we work with were a little reluctant about the cloud, they weren’t confident in its security, they weren’t sure where their data was going, and so it’s been another steady progression that over the last decade the same customers have gone all the way from reluctant about the cloud, and software as a service offering, to more of a cautious but accepting, to they’ve accepted it, and now some of the same customers are saying, ‘We only want cloud offerings or SAS offerings.’ So, I think that’s one of the things that has shifted pretty significantly over even the last decade, which just enables the software to progress faster; having everybody hosted from a single environment, making those updates as quickly as we can, I think that’s been a pretty powerful enabler for us.

22:41

And as you mentioned earlier how to effectively utilize these 30,000 issues, a great way is of course aggregating that anonymously and building patterns, which allows a pattern prediction, benchmarking, all kinds of great stuff and certainly, SaaS lends itself very well to being able to do that.

I guess I’ve already given a couple of solid hints there, but since we talked about the last decade if I were to now forecast out for the next decade, what do you think that decade holds for asset performance management. 

23:21

Funny that you teed me up for that, but I do think hopefully it’s not the next decade, hopefully, it’s a lot sooner than that when we’re really knocking out that benchmarking, and anonymous use of data for the greater good. I think that’s something from a technology perspective that I think is coming soon, and I’m pretty excited about that because each individual customer only has so many of the same assets, they can only learn from what they have, so if you have two facilities that is the depth of your knowledge base, but if you can find ways to team up with all the similar facilities and learn from everybody, I think that’s going to be pretty powerful.

But in general, I think the next decade – I think that’s one of many interesting progressions. I think another part of it is just going to be – and maybe this fits into it, it’s just how do we make this more efficient; how do you get from that wealth of data to action more efficiently? How do you get through the detect, diagnose, and resolve as quickly as possible? So, I think that’s what we’re kind of striving to figure out is to make that as efficient as possible, leveraging as little human time as feasible.

But I think the nice thing that gives me some degree of comfort is, because the technology is applicable across so many different industries, as anyone industry has its ebbs and flows and good times and bad times, I think ABM being cross-industry will have the benefit of continued progression and will just shift its focus from industry to industry as certain ones are in their good times and bad times.

25:23

Yes, well there’s a lot more common in the process industry. I should say perhaps between types of process industries versus discrete manufacturing as an example, so a lot more use cases.

One of our other portfolio companies is a company called Sight Machine out of San Francisco, and they got their start really doing benchmarking of discreet manufacturing, I think like footwear manufacturing machines. So, they would benchmark for a contract manufacturer like Nike as an example, they could look across all the machines producing their footwear globally, regardless of who was owning and managing the machines, and look at benchmarking to say which contract manufacturers are performing the best, and of course a lot of benchmarking to be able to get to that. They’ve… I don’t know, pivoted, or have been pulled into more and more process industry gigs of which would not have been an obvious play for them initially, but the modeling that they’ve done really has played in very well toward doing that. So, I think your thesis about this being very horizontal is certainly right on, based on their experience and ours.

26:32

Yeah, we’ve bumped into them actually a time or two in a couple of process industries. So, I think that is interesting for all of us, and so it will be curious to see how each industry values the vertical versus horizontal, how much does each industry say, ‘I really need you to dive super-deep into the very specifics of my industry, versus the industries that are learning or wanting to learn from other industries and have that more horizontal play, that will be interesting to play out.

27:11

Well, you guys certainly have great creds in oil & gas, paper, energy generation, chemicals, etc. and so those are all certainly hot spaces in that regard.

Let me ask, earlier you had this mantra which I love, ‘Get work, do work, make money'; in terms of the get work there, how do you know when a company is truly ready for APM, and I guess what best practices have you seen in driving APM success once they’ve adopted it?

27:47

Like about any technology, I think it seems like different suppliers leverage a similar term in different ways, and so I do think that APM can be applied in relatively consumable, or very complex fashions. We tend to suggest companies are probably ready sooner than they think they might be, because if you have an approach that’s really focused on driving action and making the math consumable, really trying to simplify the whole process, all you really need is data, and most of these process industries already have a lot of that process data. So they’re ready because they have the pain point and they’re ready because they have the data, and so sometimes it’s just taking that first step, and then they realize that it’s not as big of a leap as they might have initially thought.

28:56

So, we always start with a personal question around your own leadership journey, and in some sense, I always like to bookend that at the end and ask, how do you find your inspiration as such?

29:11

I like this question too; your bookend questions are intriguing.

Myself, from an inspiration perspective, I’ve never been much of the big dreamer of what’s out there and what could be, I tend to take more of a pragmatic approach of what’s the next thing that needs to be tackled. And so, from that perspective, the inspiration just comes from the customers. The customers are pushing to make their processes better which they’ll encounter new problems that need to be solved, and they’re not shy about telling you, ‘Here’s the problem I’m trying to solve now,’ and so frankly if you talk to enough different customers, you can see those themes of, ‘Here are the things that we need to be focusing on, and the problems we need to solve.’ So, my inspiration frankly just comes from here in the challenges of the customer.

30:15

Well, that would put you in good stead because I remember the autobiography of Sam Walton way back when, and I think he said something very similar!

30:23

Very good.

30:25

Yeah absolutely, and back to your point about steady progression in that regard, I’m sure he would have qualified as well.

So, Matt thank you for spending this time with us today.

30:37

Yeah, it’s been fun, thank you.

30:39

Oh, it’s been absolutely great, and again congratulations on a brilliant spinout here and a real ramp-up in this space.

So, this has been Matt Kirchner, Chief Product Officer of Atonix Digital, and if I might say a lifelong practitioner of asset performance management. Thank you for listening and please join us next week for the next episode of our digital industry leadership series. Thank you and have a great day

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