A Digital and Data Mindset – Digital CxO Podcast EP83

Hello and welcome to the digital CXO podcast. I'm Amanda Ani, and with me today is Mike Baard. How are you doing today?

I'm doing great. How are you? Doing well.

We have a list of topics to share with you today, as always, and we're gonna start with getting to the digital core. And this is a couple of articles and a video interview that you can find on digital CXO. The first article I'm gonna read from it, it says, businesses can accelerate growth and optimize operations by re-engineering systems for AI operations according to an Accenture report on AI readiness and digitalization strategies.

The report also notes companies, um, that strategically invest in innovation, can redesign business processes, launch new products, and enter new markets more effectively. And then, uh, for more information on a digital mindset, I have an interview with Jay Topper, the Chief Customer Officer of Fabric who also talks about the significance of digital transformation in retail. So what are your thoughts?

Well, let's talk about AI as it applies to digital business transformation. 'cause that's always at the core of the thing. Um, the great news is that AI will have a profound impact on those digital process.

The bad news is AI will have a profound impact on those digital process. And the issue is gonna be this simple, um, the IT infrastructure required to run all these AI models needs to be different needs to, there's training, there's the amount of data, there's the io, there's memory, there's all this stuff in the infrastructure side that's not quite ready and up the snuff. Secondarily, um, the data, I mean, it's still garbage in, garbage out.

And so a lot of the digital processes that people have created we're on narrow sets of data and we need, uh, more data that's more accurate to drive these AI models. And so digital CXOs are gonna find themselves involved in deeper conversations with folks who are data engineers and data management experts. And all of that needs to be worked through and somebody needs to step up on the business side and kind of take the lead in this conversation.

Otherwise you're gonna wind up with a a million proof of concepts that are going nowhere slowly and inexpensively. And so I feel like, um, too many digital CXOs have been watching this AI thing kinda unfold. Um, but somebody needs to be at the front of this thing.

We've seen the rise of so-called, um, chief AI officers, but um, AI is a means to an end and the end is always the same. It's how are we gonna use this to create something that feels like a business advantage? Um, we are a little bit too ignored on the technology side with new toys and new bells and whistles, so we will play with everything and anything.

Um, but the time has come for somebody to step up and say, Hey, I'm in George. Yeah. And I do think it's important to have, um, a a varied team of different kinds of thinkers and professionals from different backgrounds to come together to, to help.

Yeah. I also wonder though, if we're going the other way on that, and there's too many quote unquote c-level executives, otherwise is known as too many chiefs and not enough Indians. And we're starting to see this bifurcation of titles and responsibilities and suddenly everybody's in charge.

And we know what happens when everybody's in charge, nobody's in charge and nothing gets done. This is true. So moving to the, the digital nervous system needs smarter brokers.

This is on digital CXO and I'm gonna read, um, an excerpt from that. Deployments of event driven architecture are now accelerating with over four and five IT leaders saying their company plans to apply EDA to two or three new use cases within the next 24 months, according to a new IDC info brief, uh, chart. This is on the rise.

And then we have another article, kind of the same thing. Data is an asset for business aiming for sustained growth in the digital age. Building a robust data architecture is essential.

Tarnishing data's full potential and ensuring it supports business operations and decision making. So again, it seems to always come down to data in different aspects. What are your thoughts on this one?

To the same degree, a few episodes back, um, I think we talked about event driven architectures and I know that over on a separate podcast called Cloud Native. Now Steven Foskett from uh, uh, Futurum Group and I had a conversation about this as well and invite you to check that out. com podcast page.

Um, here's the problem. We have had event driven architectures for decades, um, but we're now trying to drive, um, 10 times as much data through a small pipe. And a lot of these event driven broker platforms were designed for a different era.

And it's kind of similar to the conversation we were just having, but we all want processes that occur in near real time, right? If the history of it is, I don't know, 90% of the apps that we built are what we call batch oriented. Batch oriented means that quite literally we update them and batches.

This is why so many digital processes are kind of outta sync with each other. You go to the store and um, uh, online site told you that this widget was gonna be available in that store and you get there and it's not there, it's because somebody didn't update that application in near real time. So ultimately we want an event driven architecture where every time something is sold, it automatically updates the website.

And so customers are not misled. When we get to ai though, again, we're gonna be collecting a huge amount of data at the edge. We're processing more data, uh, and analyzing it at the point where it is created and consumed than ever.

And we're gonna start deploying these things called AI models, running inference engines on those same platforms. We're gonna have to update the platforms, but all of that stuff is going to need to be processed in real time. And then the aggregate result of that needs to be shared to some backend system using some sort of event driven architecture.

We really need enterprise architects. This is a term you probably haven't heard in a long time, but if you're a digital CXO, um, maybe it would be great to have some AI folks and a data science team, but I would argue it's more important to have some sort of enterprise architect that really understands how all these components and piece parts are gonna come together to create something that feels like a fabric that you can actually use to drive the business. 'cause otherwise you're gonna wind up with all these choke points and event driven architectures and these brokers are probably at the front of the line for things that are gonna become choke points if you're not careful.

Yeah. And it seems everything is moving so much more quickly and users have a lot higher expectations. Yeah, the the trouble is these things are not cheap, so the cost of playing the game is getting higher and higher and that's a difficult conversation to have with the board.

Yeah. They have to really lay out, um, the return on investment and um, have a well thought out plan. We can hope.

Alright, so moving on. This is about, um, electric vehicle charging. So a little bit different direction now.

Uh, this is on digital DXO and it says electrical vehicle charging is experiencing an open source revelation. That's a good thing because electric vehicle charging needs one. It's not just that there aren't enough chargers, though that's a part of it.

It's that public ev charging continues to be a pain in the rump. So what are your thoughts? What do you hear from people on this one?

There you go. So I want to ask you, is the changing direction, was that a pun intended? Well, we'll just take it from what we got.

Um, there's a lot going on in this space and in fact, um, there's a recent Textron gang episode that talks about this as well. I should check that out. It's running this week.

Um, the thing is, is that, uh, the infrastructure for charging these vehicles is not up to snuff. That's basically the issue. And it's fine if I charge the vehicle in my house and it's fine if I can afford two vehicles maybe, and one I'm using for shorter distances and one I'm using for longer distances, number of, uh, perhaps that might work for married couples with a certain amount of income.

But, um, most people only have one car because, well, there's only one of them and there's more of the one-offs than there are families. So, uh, not everybody's gonna buy two cars for the purpose of just being able to charge one better than the other. The price points of the cars are coming down, but the inconvenience rate for, I don't know, taking a road trip and driving in one of these things and let's see, you get to the charging station in a, in a quote unquote, uh, what we used to call a gas station anyway.

And, uh, chances are that the charging thing is broken, so you're not gonna be able to charge as quickly as you had expected. So you'll probably be downgraded on the amount of, uh, wattage you can get to. And um, you'll sit there for a couple hours trying to charge your vehicle on a 300 mile route road trip or whatever it's gonna be.

And then maybe you'll get lucky and you'll get to a hotel and the hotel will have some, uh, charging capabilities. But there's probably only three slots open and there's 200 guests and maybe 20 of them are trying to charge an electronic vehicle. And oh yeah, I'm at India driving the gas powered vehicle parked in the charging vehicle lane anyway.

So now you're gonna sit there and you can't even get access to the bank. And when you put all this together, I mean, everybody likes the idea and the price point of the cars are coming down and gas powered and that's great, but it feels like it's just not quite there for everybody. And, um, some of these open source technologies that we're talking about in this article are a piece of that puzzle that we need to kind of sort out.

But um, we're just kind of haphazardly working our way through all this stuff and I gotta hopefully someday we're all gonna standardize on the same charging interfaces that Tesla came up with, but that might take a while and the automotive industry doesn't move all that fast. So I just don't know if now is the time or if we gotta wait another couple of years. Yeah, well I know it's certainly an issue.

I live in more of a rural area of Texas. I mean the city I'm in, um, anything within miles is just smaller towns. And so while there's interest in these electric vehicles, and we do have a few here, but the problem that I hear from many people is there's, there's hardly anywhere to charge these vehicles.

So if you're, if you are in rural areas of Texas trying to drive a great ways, you really have to map out where you're going to ensure you're gonna even have a place to charge up. So we need a lot, we need a, a solution to this. And, and I don't see any electric charging stations at hotels anywhere that I've been.

So this is the problem. And, and yeah, even in my own HOA, they were beating up my neighbor because he hooked up a charger station, but it was facing out towards the front side of his garage instead of being attached to the side of the house. But then that added more distance to the cord than he needed.

And um, you know, wound up being a silly argument at the end of the day, but I don't, you know, there's just all this noise in the system still and it's not as smooth and as easy as mere mortals want. Yeah, not yet. Maybe there will come a day though.

Uh, moving on. So the need for better telematics data for fleet management, uh, this is again on digital CXO, integrating data into fleet management has long been a key strategy to address new challenges of the automotive industry. Traditionally, fleet operators have relied heavily on data derived from hardware dongles, a practice that was entirely justified when the number of vehicles on the road was fewer and data volumes remained manageable.

Fast forward to today, however, with a colossal influx of vehicles and an unprecedented surge in data generation, the use of O-M-B-O-M-O-B-D devices no longer aligns with the current demands of fleet management. So what are your thoughts? Yeah, this is spot on.

What's happening is, um, there are organizations that manage fleets of cars and trucks and whatever they may be. And theoretically all of these things, you know, they're kind of the similar to airplanes. They're kicking off data that we can track and, uh, analyze to determine when something might break down before it actually breaks down and all those good things.

But the mechanism for collecting telemetry data is still proprietary and based on technology from yesterday. Um, it's something that we should look at in terms of, look, the way we collect data, is that a proprietary advantage or is that something that should just be open sourced and we should figure out some way for everybody to be able to collect the data. 'cause the value to me is the analytics that you're providing.

It's not the mechanism for collecting the data and if you make that difficult or you charge people for it, you're kind of just getting in the way of the outcome. So I think that this article is spot on. It's an area that a lot of people may be overlook not thinking about, but um, seems to me we need a standard.

Yeah, I agree. Uh, I think, uh, um, you know, and this kind of pertains, so I think an area that I feel might still be lacking a little bit is, um, the, the fuel tanks. Um, the fleet fuel tanks, because I always am finding gas stations being empty on gas and that's definitely a, a real time data gathering issue and, um, technology issue because, you know, really when, when you're outta gas at a, at a convenience store, that that's a a profit problem there too.

It is, and it's bad for me 'cause I'm always the guy trying to, you know, drive his car down at the e level as much as possible. And so if I could turn around the corner and suddenly you're outta gas, I may have grossly miscalculated. Yes.

Okay, so our last topic for today is the supply chain. There are growing challenges that enterprises are struggling with as they try to manage their supply chains in an increasingly volatile world. And there is a critical role that advanced technologies could play in easing this situation.

Investing in supply chain technologies, including AI and machine learning based offerings is one solution. So what are your thoughts with the supply chain? The problem with the supply chain is the only time we really think through what we should be doing here is when there's a crisis.

By the time the crisis arrives, it's too late to do anything about the supply chain. And then the crisis subsides and everybody forgets about it. I think we gotta like take a giant step back and everybody's gotta look at their supply chain strategically.

It's probably the thing that makes your company live or die at the end of the day. But, um, I'm willing to wager it's a hodgepodge of stuff and it's hard to onboard new suppliers. So, uh, even if there is a crisis and you could find new parts, you might not be able to actually get that transaction going in time and those parts will disappear because everybody else is chasing those parts.

Um, we, it's just kind one of these things where businesses tend to just, uh, blindly operate on standard operating procedure and they don't take that moment to take a giant step back and say, how do we create a supply chain? It's not really a supply chain, it's more like a network where everything does have a redundant set of components in it. Or, you know, will a flood in one location kill every supplier that we have?

So even if we had three suppliers or something, it turns out that they all got wiped out by the same thing, which is always a high probability. So are we globally distributed enough? Do we m enough stuff in the various places where we sell stuff?

Can we make an assemble stuff closer to the point where we're selling it? These are all digital transformation conversations that digital CXO should be having. There's a tendency where the folks who run that perceive themselves and rightfully settle, they are longtime experts in that space.

And, um, they'll tell you they know everything there is to know within the confines of the software they have, but I don't think that they're thinking about it from a, um, shall we say, in software. We have a concept called Chaos Monkey, where basically we go in and we deliberately break stuff and see what happens. And I think supply chain folks should be playing around with this Chaos monkey idea and just start going into your supply chains and pretend you're knocking something off and it's not gonna be available.

What are you gonna do? You'll soon discover that you probably don't have as great a contingency supply as you think. Yeah, absolutely.

You know, testing all those points along the supply chain. And where's the, the lack of connectivity? I mean, I mean, you know, it's crazy if you think about it, that a container ship knocking out a bridge in Baltimore can have a catastrophic disruption of the supply chain to the extent that it does.

It's just, you know, that's just core planning. There's no other way around it. Yeah, absolutely.

Well, that brings us to the end of today's list of topics, and I'm gonna ask you, Mike, what are your final takeaways? Uh, we need to collectively be more proactive than we're being. I think there's a tendency to kind of show up and say, well, these are the toys we have in hand, and let's go work with what we have.

By the time you go do something, you know, it's a two year window, probably the execution. So think about where's the tech gonna be in two years and start, you know, as they say in hockey skating to where the puck's gonna be, rather than trying to score a goal from, you know, 50 feet out. All right.

You heard it. So that's all for today and until next week, have a wonderful week and let us know what was the most interesting to you this week. What do you wanna hear about in the future?