SUMMARY KEYWORDS
industry, mcdonald, data, digital, twin, matt, capgemini, retail, conversation, talking, world, facility, call, solution, sensor, clients, today, hospital, technology, simulations
00:03
Welcome to the Industrial Talk Podcast with Scott Mackenzie. Scott is a passionate industry professional dedicated to transferring cutting-edge industry focused innovations and trends while highlighting the men and women who keep the world moving. So put on your hard hat, grab your work boots, and let's go.
00:21
Alright, once again, thank you very much for joining Industrial Talk and the your continued support of a platform that truly celebrates industry professionals. All around the world. You are bold, yes. Brave. Yes. You dare greatly. Absolutely. You solve problems, you collaborate, you do everything that I think is just absolutely worthy of celebration. That's why this platform is here. For you. We are broadcasting from a crew and insights. It is in Nashville, it is at the Gaylord, which is another state it's just a whole another state and everybody has the same story. And it is I don't know where to go. That's the story in a nutshell. Matt is in the hot seat. This is take two because we were having camera issues. And he's kind enough to just roll with him. Let's get cracking. All right. Tell me about yourself. Give us give the listeners a little 411 on who Matt is. Again,
01:23
again. Yeah. So Matt Brada with Capgemini global systems integration management company live in Austin, Texas. And I am a vice president in our digital transformation space, which is a kind of a short way to say that we help companies reduce their manual processes and you know, enter the 21st century. So a place like Accruent, it's a good place for me to hang out.
01:58
And, and, and he chose the he was the short straw winner of being on the Podcast. So that is cool. I like it. I like the digital transformation. How long have you been with Capgemini?
02:11
About 10 years?
02:12
10 years? Very good man. Like that. All right. So you're here at this conference? What what is your just your general impression of what people are talking about from the just like, we need help in we tell us about that? In the sense of
02:30
Yeah, yeah. It's, it's interesting. Regardless, the the type of conference math the partners I'm dealing with, or the clients who are coming to the table, at the end of the day, everyone is really bound together with an ultimate. Single Issue, right? Yeah. And they have to get work done. Right. That's what we all have in common. Right? Whether you're a government worker, or private industry, you have to get work done, and how you get work done. The pace you get it done, right, the efficiency, you get it done. And, you know, all of that's maybe different. We have industry software for that. But what everyone has in common is that they don't have a source of truth. Right? Like data, data, how that data rolls up, and aggregates and what you can do with that data. Once you know what you're doing, what your teams are doing, how well they do it, and how fast they can do it, how much they can do. Until you start getting your arms around that that insight. You're never going to advance.
03:43
That's heavy lifting, just FYI, anything when you start talking about data, collecting data, cleaning legacy data, that's heavy lifting. And I understand that, do you guys ever get to the point where like, we could go all the way back to the beginning of time and clean and scrub the data going forward all the way to the current time? Or is there just a sort of rule of thumb to go? Let's go back five years, let's, let's go seven, seven, seems like a nice number. Let's go back to and clean the data so that you do have a, a trustworthy set of data to create and make, you know, make decisions. So there's some sort of rule of thumb. Depends on the client, you're going to say
04:27
that and the industry and how much auditing you know, they get in that industry. But I would say seven to 10 years is kind of like what you're what you're supposed to do with taxes, I suppose.
04:42
Yeah, you had to bring the tax in. But tell us we were talking offline. We were talking about industries. Define retail. What that's where you work. That's that sort of in your wheelhouse. Define the listeners from from what retail means to you?
05:09
Well, you know, in today's connected world, that's that's a kind of a harder question to answer, right. In retail we have, we have b2b right business to business. And then we have b2c right business to consumer. And there used to be pretty dramatic lines on how the two of those industries within retail operated. But in today's e commerce, digital world, those lines blur, right, quite a bit. And I think I think that in the retail space, the, you know, who wins, there is who personalizes best, right? By that I'm talking about personalization at scale, right? When you go to Amazon to make your order, you know, if you bought, you know, a red dress last time, they know that, right? And then they're going to, they're going to recommend maybe the blue dress or the bracelet that goes with that red dress. And the way that they do that the technology platforms that they use, create an experience at scale. That is the you know, kind of the heartthrob of where retail is going to such a point now that we're a lot of our clients are delving into the whole notion of digital twin in the retail space, right? So if you want to go try on that red dress digitally, you can do that in the digital twin.
06:49
See, and I don't know how they know it. So when I go online, and I buy something from Amazon, all of a sudden, I've got 75 Other new, hey, how about this? What about this? Yeah, and that whole algorithm behind the scenes that I can't see? And then I go to and then I go to Whole Foods, then I want to buy it? Absolutely. No. And then all of a sudden? Yeah, I kinda like that.
07:18
Well, it's it certainly makes for a more meaningful shopping experience. And the technology we use for this or, or that marketing department uses is called social listening. Right? And they're there. It's like the, the CIA of, of the social media platforms. They know what you're, what you're typing, they know what you're discussing. And they use, like the algorithms you mentioned a moment ago. Yeah.
07:47
Let me ask you this. Your partner with a current? Yeah, are? What does that mean? What does? What does that? How does that relationship look like between you and accrual?
07:59
So recruitment is pretty much the industry leader in facility at scale management, right? So the more complicated your brick and mortar space is, whether you're an oil and gas refinery, or a hospital or shopping mall or office building. The more complicated your brick and mortar facility is, the more likely that you need a solution that occurrent provides. If you're a QSR, which is a quick service restaurant, thank you. Right and you have a franchise model so take like subway or McDonald's or write any of them. And you're and you're trying to methodically take or franchise owners through the branding experience, right? So everything is done consistently. And McDonald's on one end of the country looks and feels the same as McDonald's on the other end of the country. So the way that they do that, that standardization, right, is they have to have a common platform. common repository of truth we talked about a moment ago, accrue it in the for the facility management space, is that source of truth.
09:17
The McDonald's just as a as a point of reference, I was in China had to go I went to a McDonald's. And it was the same and even had the same smell. Right? Oh, it's just crazy. It is. It's, it's it's brilliant. Don't get me wrong. And I went to I went to the McDonald's specifically to say, Okay, I've been eating some unique food here for a little while. I just need something a little bit more. Domestic. Right? They go, they're like, Wow. Yeah. So I'll take that Egg McMuffin in China, China, right in the middle of nowhere. That's crazy. Yeah. No, it's It's fascinating. So with your with your relationship with Korea What? What does that future look like? What are you seeing out there? What you spoke briefly on digital twin? What are the things are you looking at? Just because I always get fascinated by the fact that there's this, there's the speed and the technology side, and then the human side, which is the adoption of it. And, and I have all my other challenges over here. So they don't ever really, they're hard to line up. And as as technology continues to, we can do this. Now look at how about this use case, and it isn't, you know, like, like, chat GPT just decided that they flip a switch and everybody's like, whoa, so what, what do you see in that in that area? From a future perspective? What's getting you excited? What, what do you think is sort of that trend?
10:51
Well, waste in facility management, okay. Is, is probably the number one stress factor for, for, you know, operational managers. And, and I don't mean waste, like trash. I mean, I mean, waste, like, overused H back, right, for unused conference rooms, or water that's left on, right. It wasn't shut off all the way, things like that. Now, in today's world, you see a lot of those solutions already in place, right? You go to a public bathroom, and there's a sensor, right, and you can wash your hands and the water automatically stops. So simple things like that are now done commonly, but 20 years ago, that wasn't common. Right? Right. And you would hear of bathrooms being flooded, right? Because someone didn't turn off the water. So this has been kind of sneaking up on us this, this whole IoT sensory stuff. Well, the next generation of that is being able to cut down on like service calls. Because now you can do predictive maintenance, right? We have sensors or crew in a crew, its products, right? Provide sensors to these massive office buildings that, that tell the operations manager if something is amiss, right? In that age back unit, right, for example. And they can deploy someone out to go look at it monitor, fix it before it becomes a $20,000 problem. Right. And so that that whole idea of being a predictive analytics is huge. same would apply in a hospital. Right? If all the hospital assets or inventory? Like the the, what do you call the paddles? Right? Yeah.
12:51
Oh, I'll go with it. Yeah, there's not a doctor. But I did stay at a holiday. Yeah,
12:55
I play. I play one on TV I try. Yeah, so you know, if those are if those are asset tagged in an improvement system, well, then those can be compared against all of the other panels across all hospitals across the world, right. And it will give a hospital administrator a pretty good idea of based on the age of that paddle and how long they've been in service and how they've been maintenance, what that history was, like, what their utility is, for end of life. Right? And that's, that's insight that operational people have never had before. Right? Another example, would be at, if you're an airline, right? The cost of having an engineer go up into a turbine engine, and go inspect something is fantastically inconvenient, and expensive. The whole, you know, the whole plane is down, right? And when that plane stop flying, it's very expensive. Well, now with a digital twin replica of that engine, you can see the engine in real life, just the digital twin of itself. And they can actually monitor the diagnostics that way.
14:12
But you have to have that all baked in beforehand, right? Or can you sort of do a an existing asset, and then get that level of detail? Or is that something that has to win in the digital twin world? In the example of the jet engine? Yes, I like that. I like the safety component to that. But can you take existing in start to because it's all monitored? Right now, or do you have all the it's already pulling data? You're just putting it into a digital twin framework?
14:46
That's right. That's right. But this is where the industry is going. Right? This and we can kind of compress it all and say it's, it's it's it's pretty, it's predictive engineering management. That's where a crew is going As a company, that's a large part of what we're studying and discussing at this conference. And it's certainly where our clients at Capgemini want to go. Right? They want to get ahead of whatever that work is, right, whatever their work product is, whether it's maintaining an engine, right, thank you, or an H back unit, or monitoring their hospital equipment, right? I mean, whatever it is. And so accruing is an important component for us as a management consulting company, because now we don't have to go custom app dev solutions for everything, right, we can take an industry best practice, make it a framework and present a cohesive solution.
15:44
Yeah. Do you have conversations that are around and this is sort of in line with that digital twin to be able to run simulations to and to be able to sort of run those simulations in a way that truly optimizes that whatever that asset, wherever that line, whatever, whatever you're simulating by plugging in some data here and there, and then make that optimize and then take that digital, put it into the physical guys are, are you running some simulations in that sense, too?
16:15
Yeah, we run probabilistic simulations all the time. We call it Monte Carlo. Yeah, sure. Yeah. So what are the odds of something happening? Right? And if if that something happened, what would be the impact of it? Right, whether it was cost or
16:33
C, defined? Do you think it's are we at still sort of the the beginnings of, because I still, I think they're still, we don't even know. I'll just, I'll share. So my conversations four years ago, are completely different than they are today. Oh, yeah. And and they've always been somewhat around, you know, asset management, the technology, the innovation, conversations, whatever AI, we were having conversations back then about AI, but it was still sort of a, hey, we need to put some framework around it just because it could do this anyway, today. Yeah. I still think that we we just, we don't even know some of the is still relatively new. I just think that we're still going as this forward this blasting forward with just stop. I don't know if you agree or do or we're not very bad. Whatever it is,
17:32
we are there in a lot of ways. I'll give you an example. Yes, we can now take an accrual Facility Maintenance Solution, right. But on top of that, some machine learning some some AI, as you say, train the model, on how we want it to behave. And when a sensor anomaly comes into the system. It can make a decision, who to call, what what the problem is, how to deploy it, how to resolve it, and then tag a real person at the end.
18:03
I want it to be a part of my refrigerator. So we're just knocking on the door. Hey, we noticed that the compressor has gone causing some issues today. So I'm here to help you fix it. And it doesn't go bad and I don't waste food. That's my dream. How do people get a hold of your mat?
18:22
We'd love to keep the conversation going. matthew.Brada@capgemini.com
18:28
You were absolutely wonderful. I enjoyed the conversation on. All right, listeners, we're gonna wrap it up on the other side, we're gonna have all the contact information for Matt out on Industrial Talk. Stay tuned, we will be right back.
18:41
You're listening to the Industrial Talk Podcast Network.
18:50
You know what the action item is, you know what your to do list needs to include that reaching out to Matt Capgemini is the company. And that was fantastic conversation. I'm telling you, I'm living the dream. And you can live this dream with me because it's all about getting that message out that information out that education out there so that we all because of Matt, and others, these leaders, we can all just succeed because we're all just bringing in that great information on how to do that effectively and solve problems reach out, that's something and then we as you can tell, accrued inside was the location, fantastic event. And when he 24 needs to include that in your plan. So reach out to a crew and insights and be a part of that. That event. Be bold, be brave, dare greatly hang out with Matt change the world. We're gonna have another great conversation coming from that event.
