Putting Industrial IoT on the Fast Track
In this informative webcast, Bill Podrasky, senior manager of go-to-market specialist for IoT with Amazon Web Services, and Ricky Singh, vice president of IoT-Americas with Software AG, joins our host Joe McKendrick to discuss ways to put industrial IoT on the fast track to success.
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Read the Transcript
RTInsights: Welcome to our webcast. I’m Joe McKendrick your host for today. I’m an analyst and contributor with RTInsights. And I’m very pleased to be joined today by Bill Podrasky, Senior Manager of Go-To Market for IoT with Amazon Web Services. And also joining us, Ricky Singh, Vice President of IoT Americas with Software AG. And Ricky and Bill will be discussing how organizations can put industrial IoT on the fast track.
Emphasis on industrial Iot, I should add, and this is part of our ongoing series of discussions with industry leaders on the trends shaping today’s and tomorrow’s organizations. Bill and Ricky, before we dive into this discussion, why don’t you briefly tell us about your your work in this area? Bill, we’ll start with you. Tell us a little bit about yourself.
Bill Podrasky: I’m sure. Thanks very much, Joe. So I have been working in the IoT and M2M for almost 20 years, and through that journey I have worked with both companies that deliver SAS-based platforms and companies that also have been more on the the edge sensor side. So I’ve been able to take the journey. I’ve lived in the trenches of IoT and it’s been a lot of fun and I can hopefully share some some insights today.
RTInsights: Great.
Ricky Singh
Ricky So you you are having us in great Be here doing well. Thank you. So like Bill, I have also been in the Iot space before it was called Iot. And as I zoom out, I have actually had the pleasure and the opportunity to involve be involved with many different aspects of the Iot value chain. Presently, at Off, Craig, we’re focused on the platform, so this is almost the patty of the burger that holds the meal together.
But in the past I’ve helped in, of course, Communications. I spent a number of years at T-Mobile and Sprint looking at the Internet portion of the Internet of Things and what cellular connectivity, 5G and these low power wide area networks are doing. Prior to that, I was at Accenture for a number of years doing strategy consulting around mobility and IoT.
And in that capacity had an opportunity to work with device manufacturers, chipset manufacturers, as well as keenly focus on the business outcomes or the applications that Iot drives. And now it’s I get to bring it together and work with IWC and our customers to help accelerate their time to market in value in the industrial space.
RTInsights: Great, great. It’s great to have you guys here. And you know, when I think about the Internet of Things Iot, I mean, it’s been on the sea. I’m going to date myself a little bit here. I first heard the term back in around 2008 or 2009 or so. And I thought, you know what? I wonder what a very weird name, you know, Internet of Things.
What the heck is that? You know, But the term kind of grows on you. And, you know, when you use the the word thing and appropriately enough, it’s it’s a broad term. It’s extremely broad term that describes all those devices, sensors, you know, systems that are there are there are being interlinked out there and, you know, software. AG And Tim, lastly, you know, certainly a an early path in this space, you know, into this frontier.
You know, you had you know, you guys have been in the forefront of the industry forward movement, for example, which seeks to basically connect everything together, you know, to have one well connected networked industrial society, if you will. And well, we could why don’t we, you know, start with you It talk about where Iot has been and where it is now.
You know, what is the state of IoT.
Ricky Singh: Yes. I was trying to think back to what I was doing in 2008, and that gave me a headache in itself, Joe. But you’re right, the concept wasn’t new. I think the term we put around it was new and it was called M2M or telemetry, as Bill said before that. But what was really fueling the fire was in around 2008.
You’ll remember the smartphone came out that that’s become so ubiquitous to many of us, we can’t remember our daily lives without it. I once had a police officer told me he could leave his house without his gun, but not without his phone. So that should tell you the importance that these things came and brought into our lives. But that kicked off a variety of these tangential trends around it.
One of it was the number of sensors that were in. Even the first Apple iPhone were far greater than anything we had seen before. A gyroscope tell temperature, humidity. And as the smartphone market took off, these sensors became cheap because they were in almost everything. In addition to that connectivity, Right. Mobile Internet as we knew it before you recall, your BlackBerry was really only good at sending small bits of email.
Now, we were interacting with applications very differently than we were before, and that cost of connectivity started to go down, the cost of storage to now generate, you know, all the pictures we were taking with our phones and GPS navigation we were doing the cost of storage went down and IWC certainly, you know, seeded the market with cloud as we came to know it.
And that is what sort of manifested into this term called Internet of Things. And depending on the publication you read, it was in the billions or trillions, everything just looked like a hockey stick to the right to your question of what stage are we in now, I think a big part of the beginning of that was just hype.
There’s every technology that comes to really be known as we know it today goes through what Gartner calls the hype cycle. And Joe, we had shared with you sort of, you know, my adaptation of this is that it’s felt a little bit like a roller coaster ride in that hype cycle. Initially, we think everything that can be connected should be connected.
We enter this sort of peak of inflated expectations that Iot is going to solve for world hunger in many ways. And then we spend a lot of money at it and realize, okay, you know, there’s problems, things aren’t interconnected, things aren’t compatible. I can’t scale this. It doesn’t work. We go quickly down, okay? It’s not what we thought.
And that’s really this, you know, trough of disillusionment where we recognize, hey, this is actually harder than we thought it would break, but made it through that. That took a long time. It took about eight years for us to stop, you know, having projects that were proving concepts in the stage that we see now is that Iot is actually delivering results.
It’s become a key part of many organizations. Digital transformation and software. IAG, as you mentioned, is sort of our motto is empowering the truly connected enterprise, whether this is connecting existing data that may sit in your applications, whether it is thinking about your business processes or connecting the unconnected through our Iot capabilities, we aim to provide enterprises with the toolset so that they can focus on the business outcomes that they want to drive with the technology.
RTInsights: Yeah, I remember in the early days and I guess a lot of these things had passed, you know, the concept of the refrigerator, the smart refrigerator that tell you when you’re low on milk and automatically order something similar from the grocery store or, you know, you even have smart toothbrushes that, you know, are kind of connected. But on the industrial side, of course, we’re talking about some heavy duty things.
And, you know, Bill, you know, what’s your what’s your take? You know, what’s your perception of how far we’ve come so far with Iot?
Bill Podrasky
Yeah, Well, like Rookie said, you know, I think it took ten plus years to evolve from just connecting things. So, you know, I had the opportunity to work at Electric camp, which was an early Iot company, and then Alien that works. And almost to the opportunity, customers were just trying to figure out how do I connect my device and just control it.
They weren’t really even thinking about the data side of it. And so that took a long time to go through that progression. You know, where we right now, like Ricky said, we’re very much from an outcome solution perspective and I’ll give you examples around industrial. So, you know, we had eight of us, you know, we’re we’re engaged with many, many, many industrial customers.
And so the use cases and themes are clearly around now, you know, AC performance management, connecting these assets quickly and then getting insights from the data either through, you know, email, A.I. and others. And then, you know, there’s a huge opportunity in story and migration, which is all these data that manufacturers in their facilities, in their factories collecting that data, bringing them, homogenizing it, and then gaining insights on that.
And then you have use cases like predictive maintenance and prescriptive. So, you know, those are areas that companies are actually deriving value. When we when we speak to oil and gas companies that are that are truly using Iot as part of the data strategy or part of a digital transformation and getting those insights and this becomes part of their operation plans on a yearly basis.
So it has moved from, you know, as Ricky said, like Policy Science Project, where just the engineering teams are doing this to it’s at the executive level on how are we going. They don’t necessarily talk about IoT, they talk about what are, you know, what’s the strategy. One of the outcomes as part of our broad initiatives at the company and then IoT is is is the fabric within that.
So we know and it’s interesting eight of us. Sure. You know we have a set of Iot and services and we enable that’s the classic companies like software AG But when we talk to executives, we talk to executives about what are you trying to accomplish with your strategy? And you know, what are the big rocks that you’re trying to solve in the business?
And then we know that Iot has to be a part of that because you have to get your data from somewhere off of the sensors and the voice. And so it’s really evolved from that. Let me just connect. One device or set of devices to it is now part of where we’re instead of engineering to now it’s part of the thesis we on outcomes that are impacting companies revenue and operational efficiencies.
RTInsights: Yeah, that’s a great point. And also a great point that, you know, you don’t want to try to sell Iot into the business. You got to sell, you know, how how they’re going to expand their markets and you know, be able to strategically position themselves in ecosystems, things like that. That’s that’s a great point. And it seems the proposition for Iot, it is really compelling.
The value could be amazing, but it seems it also can be overwhelming for businesses, you know, particularly small and medium businesses, you know, not to mention large enterprises, but the idea of getting out there, doing and having the infrastructure for this data, you know, being able to connect with your partners, being able to validate the data that’s coming in, you know, what are the things that are holding companies back at this point?
You know, what are the the roadblocks, if you will, that are, you know, kind of have kind of slowed things down?
Bill Podrasky: Well, I think from from our experience and perspective in the US, it tends to start with, you know, what what is the what’s the strategy in the plan? Because you need to to look at outcomes from the beginning and then you need to set expectations about how to achieve those outcomes. And in the time frame, what we often see is because we’re always working backwards from our customers trying to set their expectation up, okay, if you want to deploy early data strategy or digital transformation strategy strategy within your factories, you know, we can’t obviously boil the ocean.
We need to break this down into projects that can be delivered with KPI on and outcomes. So, you know, you may want to accomplish a three year strategy of optimizing your factory floors, but we need to break that down into a set of initiatives that can show results initially and then we build on that. So that’s really important for us.
When we work backwards from customers, we try to prevent them from trying to get to the three year outcome in the first six months because it takes time. And I think a lot of that, Joe, is really setting core expectations crawl, walk, run. How do you want to define it? Because we need to make sure that they’re seeing success from the beginning, even if it’s small little steps toward that bigger outcome.
RTInsights: And one of the things I hear a lot about I know there’s been a lot of efforts to resolve this is the the standardization. You know, every every component maker, device maker, whatnot, has had their own formats and protocols. And, you know, I know there’s been some work on higher levels to kind of bring that all together. Are you seeing progress of that?
Is that still an issue, the standardization of all these devices and the data that’s emanating from these devices?
Ricky Singh
Yeah, Joe, from my perspective, I don’t think we’re ever going to solve for that. You said yourself that things can it can be a multitude and each industry or each protocol or each type of device is going to require its own constraints. So rather than trying to standardize everything, which I do think is a bit like boiling the ocean, it’s trying to figure out how do you interface with these types of devices in a repeatable fashion, right?
But that part I think we can solve for. I often think in webinars like this I might get chastised for saying this, but the technology’s almost the easy part, right? As Bill mentioned, if you don’t start out with the desired outcome and then think about incremental steps of what business value or customer experience or regulatory compliance that you’re going to drive with the technology, no matter how well you do it, you’re poised to fail.
So a very simple way to think about this is we don’t run proofs of concept because in a vacuum, in a silo, the technology is going to work. We want to run proofs of value and you can only run a proof of value if you first define what value looks like and bite off a piece of that to prove to your customers.
In other part, I think outside of the standards aspect, it is just navigating the ecosystem can be incredibly complex. You have device and component makers, you have connectivity options, you have platform options. Do I want to build, do I want to buy, Do I want to buy? Then build? So I think navigating that ecosystem can be difficult. And this is something we as a U.S. software AG often tell our prospects is, Hey, we want to be your partner in this journey.
And if at any point we recognize that we’re not the right partner for you, hopefully we’ll still be able to steer you in the right direction. And you would have learned something from our years of experience and helping customers in the same way. The last one is, I think, messaging outcomes, and that’s messaging to your customers as well.
A lot of companies tend to get fixated on the technology or the shiny object aspect of Iot and want to be looked at as a thought leader in their space, and they’ll start talking to their customers like, look at this Iot thing that my equipment or machine or thing can do in their customers could care less because what they’ve missed is, well, how does that make my life easier?
How does that allow me to deliver more widgets or increase my customer experience? So, you know, going back to the what is it the we’re actually trying to solve for here? What are the nails that we want to hit with that Iot or that matter for us? And that approach generally addresses a lot of the inhibitors that we see customers experience on their Iot journeys.
RTInsights:
Okay, great. Well, suppose I’m a I’m a factory owner, you know, medium sized factory owner. I’m making widgets now. There’s too many companies making widgets these days. I have a pencil. It’s a pencil. I have a pencil factory. I come to you guys, you know. You know, I want to I want to. I want to get in on this Iot thing.
You know, I want to be able to connect with my partners, my suppliers, and even customers, you know, put me put chips in the pencils to see how they’re using. How do I start this? You know what? How can I scale and build this thing? You know what? What can you guys tell me? How can you guys help.
Ricky Singh
Me start here and, you know, talk about how we see this from a non Iot lens as well, right? Because you mentioned, Joe, you mentioned partners there and how much of building that pencil is, where do I get my graphite and where do I get my wood? For many organizations, as they may already have data or their suppliers may have data that they can use.
So we often start with does this data exist somewhere? Could be an Excel file, could be an application, could be an ERP system or an AP system. That’s where pieces of technology like web methods and stream sets from software can really help expose some of that existing data. Before you ever look at connecting a machine as an example, right?
Once we look at those existing datasets and that expose as well, actually I can’t build the right pencil if I don’t know how many hours a day this machine is running. That’s when we can go and instrument some of those machines themselves to connect the unconnected and start to expose where you can get greater operational efficiency. In that scenario, not only are we talking to the operator of the factory floor, we go to the maker of let’s assume the press that turns that would into the pencil.
We go to that equipment maker and say, Hey, did you know Bill’s pencil factory is now having to fix what you didn’t fix in the first place and retrofit your machine with some insights? There’s other customers like Bill that probably have this problem as well. Wouldn’t it be nice if you made it easier if they bought your machine for you to offer these insights to them?
But what do you think?
00:19:24:18 – 00:20:15:22
Speaker 2
Yeah, I mean, you know, in the situation like that, deeply, the operations of this factory from, like you say, that’s running through the supply channel and how do we help them not only instrument the machines but optimize the processes because likely, as you said, the data in a lot of different silos in this factory. So how do you unlock the data from the different machines and then be able to bring that together and leverage that for real outcomes to help that business run more efficiently from the factory all the way out to the supply chain?
00:20:15:24 – 00:20:54:00
Speaker 2
And so we will talk about things like, Hey, how can we help you as part of this plan, diagnose root, cause pain in your equipment, doing any type of remote monitoring, operational. And as we talk, how are we ensuring that we’re meeting your outcomes? Because the conversation will always start with the outcomes. Yeah, we have a process that Amazon just called PR Q, which is we always start with the with the press release.
00:20:54:03 – 00:21:23:20
Speaker 2
What would that press release look like? We write the press release first, then we work back from that. So we use the same methodology with customers like this example. Joe And I know that you know Rikki in software and we have a similar view of how to tease out the right outcomes and then understand the outcomes and then you know, what are what are the steps of solutions that will drive to that?
00:21:23:22 – 00:21:47:23
Speaker 1
That’s fantastic. And then, Bill, you know, Amazon Web Services, you know, you guys are all about the cloud. And I imagine nowadays, you know, a factory owner doesn’t have to worry about what the infrastructure, how much infrastructure they have to purchase, you know, servers, storage, networking, all that good stuff. A lot of it is available now through cloud services that AWG provides.
00:21:47:23 – 00:21:55:18
Speaker 1
Yeah. I mean, you guys can handle, you know, 80% of what is needed there, right, In terms of the infrastructure.
00:21:55:20 – 00:22:38:09
Speaker 2
Yeah, absolutely. I mean, we have 16 years of experience in our cloud. We, we created the cloud for our hyperscalers. And you know, that experience has resulted in a million plus customers and partners like Software Aging. And so we continue to build out the scale, the reliability, the security of building our own silicon like graviton, all the other chips that that help to drive more efficiency and the servers and the services and the managed services we have, we have over 200 plus managed services.
00:22:38:09 – 00:23:09:15
Speaker 2
And so we will continue to optimize for our customers because again, you know, we’ve always work backwards from the customer and help them look at their business from a long term perspective, and that’s the cloud. But we’re also working on the edge as well. And that’s an important aspect because we realize, especially in a factory scenario and in the industrial manufacturing world, that not all the data is going to go to the cloud.
00:23:09:15 – 00:23:32:23
Speaker 2
So you need to have solution nodes where you can process data on the edge, keep it in the location and only bring up what’s needed in the cloud. And I think that’s that’s a that’s an important optimization aspect of a complete solution that is end to end from edge all the way into cloud application.
00:23:33:00 – 00:23:52:03
Speaker 3
Yeah. And we this is something we call the edge to cloud continuum because if you were to do a survey of the folks listening to the webcast today, I’m sure you would get a number of different explanations for where the edge is. And there is, you know, there are. All right answers. The edge can be the actual end point.
00:23:52:05 – 00:24:17:15
Speaker 3
The edge can be the factory itself. The edge can be the edge of the network. It could be the data center that’s closest to that factory. What we know is Edge is not the cloud. I think that’s really the only definition that I think is all encompassing. But for us and where we’ve gotten feedback from our customers that keep velocity and software edge, you really help solve this pain point is being able to develop your application once and deployed across that continuum.
00:24:17:15 – 00:24:34:02
Speaker 3
So you have a piece of software that’s running in the end point. This could be a machine or this could be a sensor. You could in the case of a factory, if you need latency, run the entire platform at the edge. In that factory itself, run it at the edge of the network or run it in the cloud.
00:24:34:02 – 00:24:50:02
Speaker 3
With the platforms natively been designed to run, the challenge for a lot of our customers is that they are being almost forced to say, Hey, either you need to take all of this data and push it into the cloud and run it there, or we expect you to have really, you know, heavy devices at the edge where you can run the entire platform.
00:24:50:04 – 00:25:03:13
Speaker 3
And that leaves something to be desired where we feel we’re meeting that challenge by catering to this edge to cloud continuum, because every use case is going to have slightly different requirements.
00:25:03:15 – 00:25:18:19
Speaker 1
And this is great stuff. And guys, I know you you work with companies, you know, you have there’s Iot and action going on right now. You know, please tell us about some give us some examples. You know, companies where Iot is actually in place and delivering this value.
00:25:18:21 – 00:25:20:09
Speaker 2
To the.
00:25:20:11 – 00:25:48:05
Speaker 3
Worker. I think the stories I love the most are not digital native companies, right? Because when you don’t have a legacy, it’s much easier to adopt, you know, Netflix, for example, didn’t have to contend with legacy circuits, right? They were born in an era that was digitally native. The one example and we recently did a webinar along with Bill with our Customer Flex Co, there are 115 year old company.
00:25:48:05 – 00:26:24:04
Speaker 3
So those are the examples I find the most fascinating. And not only did this organization really dive into digital transformation and what that means for their customers in their operations, they did so in a way that’s really driving business outcomes and competitive advantages for them. A short introduction, they flex co make conveyor systems at mining sites, so very labor intensive and risky environments where they’re either moving concrete or moving heavy environments.
00:26:24:06 – 00:26:47:06
Speaker 3
One of the examples I believe Keith shared with us was a specific conveyor system that was nine miles long and cost $7 million. Right. In the example that they used was not having any insights into that conveyor or that belt that’s being driven on that conveyor. When it would go down, it would cost a huge amount of downtime.
00:26:47:06 – 00:27:07:03
Speaker 3
Now you’ve got people working in that mine site that can’t do anything because they can’t move materials around on this nine mile belt sometimes. That led to complete failure of equipment that they could have caught sooner had they just cleaned out debris in one part of the conveyor. And flex co recognized early on that they’re very good at building conveyor systems.
00:27:07:05 – 00:27:30:15
Speaker 3
They’re not very good at building Iot platforms. So they partnered with Software AG and AWB to help accelerate their journey. They started with what are the pain points that our customers are experiencing, things like equipment, downtime, visibility, worker safety and hazardous conditions was a big one, right? When a machine like this goes down, I now have to physically send somebody out to repair it.
00:27:30:15 – 00:27:52:18
Speaker 3
Maybe the middle of the night may lead to a situation that could put that person in harm’s way. So we highlighted the number of potential positive outcomes we could drive if our machines are conveyor, could talk to us, and then looked at what’s the easiest and fastest way for us to recognize some of that value. The premise of Kimmy lost.
00:27:52:18 – 00:28:15:03
Speaker 3
That is that, you know, a variety of different use cases that I’ve shared with you, Joe, what looks like an iceberg, regardless of if it’s a conveyor belt or an elevator or a medical device, the things that are needed to deliver that application are actually consistently the same. You need a infrastructure that’s scalable and resilient. Security not a nice to have.
00:28:15:03 – 00:28:34:05
Speaker 3
It’s a need to have in the Iot world, accounting for a lot of different types of networking, communication protocols, all of that resiliency and scalability doesn’t matter what type of thing you’re connected to it. So that’s what we provided Flex Co out of the box where we allowed them to focus on what their connected product experience would be like.
00:28:34:07 – 00:29:02:07
Speaker 3
How would their field engineers interact with these conveyor systems? What are the notifications that they would send to and get from their customers about the performance of a conveyor? And that’s led to a variety of different positive business outcomes that I won’t share here. We will ask people to go back and listen to that webinar because it is truly insightful how a 100 plus year old company is living and breathing digital transformation with Iot really being at the core of it?
00:29:02:09 – 00:29:08:02
Speaker 1
Great. That’s great stuff for my panel of companies. 200 years old, by the way.
00:29:08:04 – 00:29:09:02
Speaker 2
You.
00:29:09:04 – 00:29:13:11
Speaker 1
And Bill, what have you seen in action?
00:29:13:13 – 00:29:49:23
Speaker 2
Well, yeah, we have quite a bit of companies that I love in the industrial space. I would I would say I’m thinking about oil and gas companies that use asset performance management to improve their their operations, both of their midstream, upstream and downstream. And so think about these very large massive machines that they need for oil or gas company.
00:29:49:23 – 00:30:25:22
Speaker 2
And as Ricki said, bringing in sensors so that you’re able to identify first of all, you’re you’re able to understand how a piece of equipment is operating. And then with that data being able using your mind and you’re able to really drive insights and you’re helping these oil and gas companies save sometimes tens of billions of dollars. Because if and these to give you context, these pieces of machine or machinery are the size of props.
00:30:25:24 – 00:30:54:17
Speaker 2
I mean, they’re very, very large machines and they go down then an oil or gas company has to shut down to to fix this. And you’ve you’ve seen instances where gas companies in Texas and Louisiana have had to shut down because they have they have to repair equipment. So when you’re shutting down a gas pipeline or an oil pipeline, it’s costing you tens of millions of dollars potentially a day.
00:30:54:19 – 00:31:24:19
Speaker 2
So we have several companies that are deploying now. So performance management to proactively get ahead of those situations and be able to determine when a machine potentially is going to fail so that they can, you know, leverage that data to hear a problem or you hear a particular part of the machine before it fails.
00:31:24:21 – 00:31:51:03
Speaker 1
And that whole idea of predictive analytics, it’s fascinating stuff. You know, it applies across the trains, elevators, oil and gas, as you mentioned, conveyor belts. It’s it’s, you know, really, really going to change the the quality and the service that customers receive and looking forward to the future. You know, I want to get your both of your senses of where it’s all heading.
00:31:51:03 – 00:32:05:23
Speaker 1
You know, what’s where things going to look like a couple of years from now or even by the year 2030. You know what what what is this all leading to this this this interconnectedness, this of devices and sensors and systems?
00:32:06:00 – 00:32:25:21
Speaker 3
Move on to that section. If you don’t mind, I want to raise one more point about customers. And on their journey for Iot is I’m starting to see this a little bit more in the Flex Go example. It’s a customer that didn’t have a connected solution. So I kind of think of it as a greenfield environment for us to think about digitizing their business.
00:32:25:21 – 00:32:49:11
Speaker 3
But in certain scenarios, we’ve had customers that embarked on their Iot journey ten, 15, 20 years ago, before it was cool, before it was called Iot. But they’re getting to an era now where they’re recognizing that they’re not moving with the right agility and the speed to react to market needs in their customer demands that are really serving them.
00:32:49:11 – 00:33:11:18
Speaker 3
So I would urge listeners that just because you have a, you know, Gen one platform in place and we do NWC and Software edge, you have a common customer who we can’t mention here, but they had built their first generation platform 15 years ago and were realizing that they were spending all of their time on that below the water level of the iceberg ready.
00:33:11:19 – 00:33:30:21
Speaker 3
We’re just we’re spending all of our engineering resources and effort just to make sure this iceberg stays afloat. And that means we’re not paying attention to we’re listening to our customers for the things that matter, for the things that they’re engaging with, for the applications, the reports, the predictive and prescriptive insights. So I want the listeners to be able to say it’s not too late.
00:33:30:21 – 00:33:56:17
Speaker 3
We can migrate off your existing solution regardless of what it’s based on and help transform. We’ve done customer migrations in as little as four months and help them focus on the right value added parts. Then and only then can you start to look ahead and focus on what’s next, what comes after. As we look at these other trends that are really fueling the next phase in our digital transformations?
00:33:56:19 – 00:34:04:21
Speaker 1
And it’s all about intelligence then, right? And providing intelligence across the enterprise in everything it does.
00:34:04:23 – 00:34:14:20
Speaker 3
So thank you for allowing that interjection. I think it’s an important one. But but Bill, now looking forward, what’s the what’s next part, which is always fascinating about our job. What are some of your thoughts?
00:34:14:22 – 00:34:55:05
Speaker 2
Yeah, well, as everyone knows, obviously you have to be an ostrich not to have been involved in the general movement is really just an extension of where I am now has been going in the last 1520 years. The has been using I, I am now for many, many, many years. And so what I wanted to do is talk about where I see some really interesting gender use cases within or based on what we’re seeing from from our customers, their interest and the services we have.
00:34:55:05 – 00:35:31:00
Speaker 2
And and I’ll touch upon maybe 4 to 5 of them really quickly and then turn it back over to Ricky. But the first is diagnosing cause some industrial equipment, if you think about it, being able to use that to identify probable root cause is based on error codes generated by equipment. So these episodes that would be documented in vender equipment manuals or found online or within document management systems in general, I can help organizations generate standard operating plan.
00:35:31:00 – 00:36:02:14
Speaker 2
Guidance from those manuals, suggest standard operating plans based on alarms. So this would help speed time to resolution for incident response teams. The second is remote monitoring and condition based maintenance. So if you think about generative and enabling remote monitoring and condition based maintenance of assets that are deployed to remotely or inaccessible locations, you can create digital twins of these assets.
00:36:02:14 – 00:36:45:00
Speaker 2
But generally I can continuously monitor their performance. They can detect anomalies, they can predict maintenance requirements. These facilities proactively can then do maintenance planning, which reduces the need for costly and time consuming physical inspections. The third is operational optimization and efficiency. So if you think about how you can take anything from, you know, real time data from one or two devices that can be analyzed to identify bottlenecks, inefficiencies or opportunities for improvement, then generally I can give an simulate.
00:36:45:00 – 00:37:24:16
Speaker 2
So think about that. Generally, I can simulate different operational scenarios using digital twins and enable organizations to make informed decisions and implement changes that enhance overall efficiency and productivity. The fourth is smart energy management. I love this one thinking about how you can optimize energy consumption in buildings or industrial environments. I can analyze data from Connect, probably connect IT devices, weather conditions, occupancy problems, energy usage trends to develop intelligent energy management strategies, reducing costs, enhancing sustainability.
00:37:24:21 – 00:38:01:08
Speaker 2
And the third one is one side is, I think about generators and Iot powered virtual assistants for predictive maintenance operations, which I think is really cool. So you have a virtual assistant. Leveraging technology is like chatting on an empty and healthy ends. Things improve their productivity. So you use a virtual assistant that maintenance teams can use to gain instant access into critical information like real time equipment status, historical trends, maintenance logs and procedures.
00:38:01:08 – 00:38:29:02
Speaker 2
So those are just five examples that we have been working with here in the US with our bedrock foundation model service law. We have several large language models that are part of bedrock. And then of course design. So yeah, hopefully that’s that gets people thinking about some some good use cases.
00:38:29:04 – 00:38:33:09
Speaker 1
Great examples. Thank you. And ready.
00:38:33:11 – 00:38:33:16
Speaker 3
For.
00:38:33:16 – 00:38:36:14
Speaker 1
My year 2013. What’s going to happen?
00:38:36:16 – 00:39:03:00
Speaker 3
Hey that talking about the futures is super exciting. So it’s a key part of our roles here. So I find this question really intriguing. Three things. I think the first, there’s going to be new ways of connecting right today, you know, cellular connectivity and low power wide area networks are there. But you look at what space X is doing with StarLink and now all of a sudden, satellite connectivity becomes within reach.
00:39:03:00 – 00:39:22:01
Speaker 3
For example, Bill mentioned oil and gas operators that are operating fleets in the middle of the ocean. For them, connectivity hasn’t even been an option before, right? So I think as that happens and the cost of connectivity and the types of connectivity available for people come down, it’ll make sense to connect more things that were unable to be connected.
00:39:22:01 – 00:39:23:16
Speaker 2
Before.
00:39:23:18 – 00:39:55:15
Speaker 3
The second. I think once you’ve connected those things, the way of turning that data into insights will continue to change. It will be changed by age I and largely what language models are a iteration upon, you know, turning data sets into insightful information. I almost think of this as the A.I. dashboard, right? If you think about Iot, every demo that’s ever been done of an Iot solution, we put up a nice dashboard and it’s got some widgets on it that shows those data.
00:39:55:17 – 00:40:32:21
Speaker 3
But what that fails to recognize is who’s the person looking at that dashboard and does it actually help them do something they couldn’t do before? And that’s where I think A.I. and, you know, large language models in Gen I will almost create this ability to say, what is the information I’m looking for if I’m a CEO or a product line owner, rather than looking for the right dashboard, I can now ask an assistant like the one that Bill mentioned and say, Hey, tell me how Product Line X is performing in cold weather conditions in the Northeast for for the past six months.
00:40:32:22 – 00:41:01:07
Speaker 3
Right. That gives that product line manager a very succinct based on the data that was connected insight into what they’re looking for without having to build this dashboard that may or may not show them the information. In addition, I think A.I. is going to turn insights from data that’s being collected at the edge so you no longer have to shove all of this massive amounts of data into the cloud and then run analytics on it and then determine what’s needed.
00:41:01:09 – 00:41:22:03
Speaker 3
We’re going to get better at managing and deploying. Yeah, models. This is a core part of Cumulus to this functionality to turn that data into insights when and where needed. The last then is if we have new ways of connecting and new insights from that is new ways of doing business. And many organizations are already sort of there.
00:41:22:03 – 00:41:41:24
Speaker 3
But if I think about Iot, it’s not a destination, it’s a journey, right? So for many of our customers, we go back to why they do what they do Iot to either be more operationally efficient so save money or do something more efficiently than they’ve done before. Allow them to be compliant. This is a big, you know, stick driver varieties.
00:41:41:24 – 00:42:01:21
Speaker 3
I need to tell the government I haven’t driven more than 800 miles a day so I can show them a report of the data driven now. But the last one is new ways of doing business. So when I said earlier, it’s not about the tech. When you have this data collected in Joe, I would love for you to share what we call our maturity curve with the listeners here as well.
00:42:01:23 – 00:42:24:16
Speaker 3
You have that remote monitoring. It serves as the foundation to improve operational efficiency. Right now, I know what the equipment’s telling me before sending somebody out. Then it allows you to think about your maintenance programs and how you service the needs of that customer. But as you go up that maturity curve, many of our customers are completely changing how they’re going to market and serve their customers.
00:42:24:18 – 00:42:47:07
Speaker 3
They’re no longer selling them a piece of capital equipment. They can now go to their customer and say, Hey, you’re buying a welding robot from me. What you actually care about is the number of welds that that robot did. I now know because that robot is connected and the insights that I have from it, I’m just going to charge you by the number of successful welds you make from my robot as opposed to selling you a robot in itself.
00:42:47:10 – 00:43:07:03
Speaker 3
Right. And those are the transformative capabilities that as connectivity, as platforms become more mature as we think about these incremental steps that unlock business value, we have customers that are completely changing how they go to market and how the service their customers. And that’s what’s really exciting to me.
00:43:07:05 – 00:43:14:02
Speaker 1
And I see up there equipment as a service. EAA Yes, I love that concept that makes that’s, that’s, that makes a lot of sense.
00:43:14:02 – 00:43:19:09
Speaker 3
We’re entering a new era where everything will be as a service, which is all.
00:43:19:11 – 00:43:27:05
Speaker 1
ECAC Easy makes things easier, as in the manufacturer for the manufacturing sector. Well.
00:43:27:07 – 00:43:42:04
Speaker 2
And Caterpillar’s doing that today, Joe. And they don’t they typically are not selling their, their equipment, their equipment as a service. So we have certainly examples up there to.
00:43:42:06 – 00:44:06:08
Speaker 1
Classic fantastic at changing the face of manufacturing as well. So it’s going to be an interesting ride. Well well, I appreciate our time is run out. I want to thank you again, Bill Petroski of Amazon Web Services, Ricky Singh of Cumulus Software AG. This has been one fascinating, very forward looking discussion. And thank you very much, guys. And thank you to our audience.
00:44:06:08 – 00:44:09:05
Speaker 1
Thank you, everybody, for joining in today.
00:44:09:07 – 00:44:09:15
Speaker 2
Thank you.