Lessons from Supply Chain Disruptions and Consulting Firms – Digital CxO Podcast EP 75

Hello and welcome to this week's digital CXO podcast. I'm Amanda Ani, and with me today is Mike Ard. How are you?

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

We have some great information to cover this week in the world of digital transformation. Starting with an interview you had with, is it Tushar Patel of Clio and his advice as far as supply chains and keeping them from being disrupted? Can you go into some details?

Yeah, I mean, his point of view on it is that they're gonna get disrupted. There's no two ways about it. I mean, you can't help but explain, um, you know, there's gonna be a cargo ship then in suddenly is outta control and hits a bridge in Baltimore.

Who can plan for that? Nobody. Um, there's gonna be disruptions with, you know, rebels trying to force, uh, the sinking of ships in the Red Sea and that reroutes traffic around Africa.

Who can foresee that? Nobody, there's just always gonna be these kinds of disruptions and it's a fact of life and, um, you know, if you're supply chain gets disrupted, well, the point of this whole thing is that it shouldn't be disrupted because of these events. It's just something, you know, you have a single point of failure in your system that should not ex exist in the first place.

So I think a lot of the digital CXOs need to kind of sit down with some of those supply chain executives and play out some what if scenarios and just say, well, if this piece was removed, I guess, you know, in the land of, uh, uh, DevOps, we have a thing called chaos engineering where we just randomly pull things out to see if the system crashes or not. Well, supply chains are the same idea. It's you gotta randomly just say, Hey, what if we woke up tomorrow and this supplier was unavailable, or it took us six weeks longer to get us some part, what would it do to the business?

And I think shareholders are gonna hold these companies more accountable for that 'cause they're not gonna be like, oh geez, there was a disruption. Heavens to Betsy, who knew? And then they're just gonna punish your stock anyway and blame you anyway, so you might as well get in front of it.

Yeah, and I think all the business leaders have learned a little bit, you would think from a couple years ago with that massive supply chain disruption that was all over the news and affected so many, um, industries, especially automotive and such. And now we, we look at that with chips even. And, uh, we know that even one little bottleneck in the supply chain there with computer chips can cause issues.

So there does need to be some planning for these. Yeah. Now I'll be a little bit cynical, right?

Because, you know, uh, we'll take gasoline prices, right? So, you know, if it's, if somebody sneezes in Saudi Arabia, suddenly gas prices are up. And I, and I'm being facetious, but the truth of the matter is, there's a lot of folks out there who are using, you know, isolated incidents that probably don't have much of an impact to make a case for increasing some price on some good somewhere.

And, um, so people are gonna be a little bit more, uh, uh, critical of those moves. 'cause they're gonna be like, well, that's nonsense because you're supposed to have a better plan in place and the, to make sure that that doesn't happen in the first place. So I was just recently at the Informatica conference in Las Vegas, uh, and we talked about this a little bit last week.

So we're gonna go more detailed about the interview that I had with Jim Krueger, as well as some other, um, staff and reps that were with the company there. And the big thing in digital transformation right now, as we all know, is ai, it's a big thing. Company leaders are looking at how to integrate it, and they have a new solution integrating the Claire, which is their generative AI solution into all their, um, data management tools that it's embedded into their intelligent data management cloud.

And not to mention there was a lot of talk about partnerships. They've partnered with Microsoft AWS Snowflake amongst others, which I'm hearing a lot about. Um, you know, the importance of partnerships when it comes to solutions.

If they don't have a solution, then these partners do and they can integrate their solutions to make a a big product offering. So what did you hear about, um, this and what are your thoughts from business leaders? Well, and Format has been at this clear thing for a while.

They were one of the earlier pioneers in that space, and it was much more around traditional machine learning models applied to data management. Now they're adding in generative AI capability. And it seems like, uh, Claire has expanded to be more of a, a brand than a particular thing.

It's, there's a bunch of models that sit behind that, that you're gonna be able to leverage from data management. Competition in this space though is fierce. Everybody and his brother who has a data management platform is pointing to AI and saying, Ooh, this is gonna be a great thing.

And everybody has to get their data management house in order, and maybe a flood will lift all boats. But it does seem to me there's just no end of options in this space. So I don't know if all of them are gonna survive over time and informatic has been around forever, but, um, you know, there's a lot of new players in this space too, so it'll be interesting to see how this all plays out.

Yeah, and and I think again, the, the partnerships and the collaboration with other companies, we're just gonna see more of that as far as, you know, you're talking about one of 'em winning over another or is laying out. But I think the more partnerships we see, uh, we're gonna have combined tools available. Yeah, I would agree with that.

And, um, I think a lot of folks are also gonna stitch a lot of different tools together. I don't, not entirely clear how many folks are gonna standardize on a single platform. I'm sure they would like to, but, um, whether that's practical, it remains to be seen given all the data types that we're trying to now feed into these AI models.

Yep, absolutely. Moving on, your brother Frank was just in Barcelona for the IOT World Congress event and he wrote an article over on digital CXO about combining forces with AI and internet of things, essentially bringing together information technology and operations technology and blending them. And, uh, it's a, it's a, uh, seems to be something that business leaders are definitely looking into harnessing.

Uh, but it's kind of on the beginning that really at the beginning stages of how to do that. So what are your thoughts? Well, it seems to me that the operational technology people otherwise known as OT, have discovered ai and it's, it's still early days, but, uh, their understanding is that they're gonna be able to take, uh, some sort of inference engine that's small and run it on, uh, an ENG device to add some sort of, uh, AI capabilities.

Some of it might be predictive, some of it might be generative, depends on the use case. Um, I think what will happen is that the compute horsepower at the edge is getting stronger and robust with each passing day. Some of those things out there feel like, you know, and we used to call an entire server in a data center.

They have that kind of capability. It's still early in terms of am I gonna use, uh, traditional CPUs or am I gonna use some sort of accelerator or am I gonna, you know, maybe spring for a GPU if I can find one. Um, there's just a whole spectrum of conversations to be had here.

And the part that I'm scratching my head is, I mean, you know, with all due respect to OT people, they're not the most, uh, compute software iterate crowd in the world. They, they understand the art very easily enough and, uh, but these are a whole other generation of applications and it's gonna take a bunch of data scientists working with a bunch of developers, and then these things gotta be centrally managed. So I can't help but wonder if this becomes the, uh, uh, a fulcrum where this whole conversation about the merger of OT and it finally happens because, you know, well we've been talking about that for the better part of a decade, but the OT people have always been like, yeah, we're not so sure you, it guys know what you're doing, but we could use your help with cybersecurity.

And that was it. Full style. Yeah.

And I think it just involves, uh, better communication and collaboration between these departments. Maybe a little bit of training might be necessary when it comes to blending the two, but I think they could work together very harm harmoniously. Um, and it would be a good way to tackle many processes.

Well watch this space. It's gonna be interesting for certain. And I think, you know, when I was talking to Frank about it, he was talking about, uh, I guess there was folks who were using, uh, uh, well, they were tracking trains in Africa and they were using drones to do that.

So anytime there was a disruption in the train service, the first thing they did is they flew a drone out there to see what was going on. Uh, sometimes I guess when there's an issue with theft from the trains as well, and I guess the minute the bad guys see the drone, they start heading for the hills. So, I don't know, maybe, you know, drones will be following along on, uh, guard duty for trains, but it's an interesting Yeah, and we're, and we're seeing drones being utilized as a resource more often too, in those areas that people just can't get to or can't get to quickly enough.

So it's, it's a great solution. And they'll be embedded models and the drones talking to embedded AI models on the train, so. Mm-hmm.

It's Fun. Mm-Hmm, absolutely. So next we have, uh, an a contributed article, and this is actually on Techron ai and it's about manufacturing industry and, um, ai co-pilots helping the workers in manufacturing.

And, and we're hearing a lot more about this too, speeding up processes, automating processes, and, um, what are you hearing out there from business leaders? Well, a lot of those IOT systems that we were just talking about are on that manufacturing floor. Um, I believe there's already any, a significant amount of, uh, predictive models used in manufacturing.

So we'll see how generative AI gets, um, added to that mix. But you can envision a world where, um, you know, tell me where it's most likely we're gonna have a disruption in our service, you know, as a combination of a predictive and generative ai, uh, question because the response will come back in natural language versus, you know, some fancy chart that's a little hard to decipher. So I guess what I think is gonna happen is we're gonna see these models kinda work in concert with each other and I'll, and we'll have some orchestration layers and different tasks will be handled by different AI models and maybe we need an orchestrator for the AI models to help us with the manufacturing process.

But, um, it's gonna be, uh, interesting challenging times. Uh, but I also think one of the places are maybe for use cases for AI that we get the biggest return on investment immediately is manufacturing. 'cause it's generally more of a contained kind of thing, right?

I mean, uh, I have a limited amount of data, um, or at least I have a, a well-defined set of data that I can apply to the AI models in a way that I can, uh, guarantee at least their better output. So it's not like everything's general purpose. So to a certain degree I can keep things, uh, at least the outputs from the agenda, AI responsible, hopefully, uh, hallucinate less because, well, I can't afford to hallucinate in manufacturing 'cause well, who knows, maybe you're making yogurt and suddenly you got a thousand gallons of extra yogurt because some AI model hallucinate, that's a no go.

Yeah. And what I envision is as being really awesome is if we could have ways to where we could literally just kind of speak out loud to some sort of system and the AI is gonna just, um, respond and we tell it what to do and it, and it talks to the machinery and everything gets on track, that'd be really cool and efficient. I think we're a little far from that right now, but it'd be pretty cool if we could just talk to something, it talks to the machine and it gets done.

That's just get or done. That'll be the model for ai. Okay, so last on our list.

Let's see here. Yes, so this is a very interesting contributed article on digital CXO and it's about con, this big four consulting firm layoff, um, and how that really kind of shows the industry shift for digital transformation. And the interesting thing is that they didn't foresee it.

And so they had all these layoffs as business leaders were cutting costs and they were cutting their consulting firm, um, costs and going more with accounting and things that made more sense, um, for the return on investment, um, as they moved to digitally transform. So it was an article about tips for digital transformation in general and then, um, how you could look at NVIDIA innovation and, uh, their digital transformation process and how they have just excelled and how other company leaders could do the same. Uh, as well as why did the consulting firms themselves who are helping these companies, why did they not foresee it and, um, have such struggle.

So very interesting article. What are your thoughts? Well, I think that there's was a massive amount of investment in headcount from these companies, um, you know, in the covid era.

'cause everybody thought everything was gonna be digitally transformed. And a lot of these projects were, shall we say, ambitious and, you know, come to today and pretty clear that the emphasis has shifted to, you know, help us be more efficient and give us some sort of tangible ROI. And I think that caught a lot of the, uh, shall we say, uh, big thinkers in some of these companies off base.

And so I'd be curious to see, you know, who exactly is being laid off in these organizations? 'cause I think it's twofold, right? I think one is the, you know, the long-term fanciful thinker in those projects are probably harder to fund.

And then I also think that the, uh, services companies themselves are looking at gen AI and saying, there's a lot of things here that maybe we're in front of a little bit still, but maybe we'll cut some head count down to make the bottom line look better in anticipation of the fact that we think AI is gonna do more of those things for us. And so maybe we can cut from, uh, the bottom. So I feel like the cuts came at, you know, the super high end of the service providers and then the or manual tedious kind of jobs that they're hoping AI will do for them.

Uh, theoretically they have a bunch of consultants that can go execute some of that, but who knows? I think a lot of folks are still, you know, the jury's still out on exactly what I can do with ai, I cannot do with ai, with or without people. Yeah, absolutely.

Well, that brings us to the end of our list this week, and I wanna ask you the audience to share what are your thoughts on what we share each week? Which articles are your favorite? What do you like reading about?

So feel free to put that in the comments. And meanwhile, have a wonderful week. And Mike, what are your last thoughts?

All Right, everybody, there's a lot going on with ai. Don't let it intimidate you, keep going forward, but keep those expectations reasonable at the same time. Absolutely.

Okay, we'll have a great day, everyone. Till next week.