Skill Shortages and Data Analytics Issues – Digital CxO Podcast EP 66

Hello and welcome to the digital CXO podcast. I'm Amanda Ani and I'm here today with Mike Vard. How are you doing today?

I'm well, guys. I'm, uh, just off a flight from Paris, so it's a little ragged, but other than that, I'm pretty good. Yes, I applaud you being able to get up and do this right away, and I can't wait to hear all the news from, from CubeCon and, and all the information gathered over there.

So the first round of news that we're gonna discuss today is a lack of tech skills and some shortages in that area across several business sectors. Um, starting with an Infosys survey, which surveyed a thousand business executives. And it was very interesting because it found that 75% of business executives are concerned about the rapid technology change rate exceeding their capacity to implement these innovations.

Um, and part of the issues with that is a skills gap in being able to, to harness these new technologies such as AI and various other ones. Um, big skills gaps were in statistical analysis, machine learning, and cloud computing. So what are your thoughts, Mike?

I think the business leaders are finally waking up to the fact that, um, how dependent they've become on IT and software specifically because I can't think of a business today that doesn't to one degree or another wholly depend upon it to deliver its services. And we see it all the time when it suddenly is unavailable. It's not that the business is inconvenienced, it just shuts down for the period of time when it is being, uh, quote unquote fixed.

Um, and it's kinda, it's a little bit disappointing to be honest, because this issue's been floating around for a long time and you would think that business execs would get savvy about this. And, um, the IT skill shortage is a major problem. Now, I, I will tell you that there is some silver lining in all of this.

Um, the survey kind of looks at, you know, the willingness of the businesses leaders to invest in upskilling and it's kind of basically comes up with some members that suggest that, um, we're finally gonna see some investments in training be, and, and part of this is, I think the average business executive thinks that they're George Steinbrenner and somehow or other they're gonna find the person with the right skills magically and hire them for the right price like you would any other sports team. What the reality of the situation is, everybody's out there looking for the same talent, the same players, and um, you can't find them and they're not gonna go get skills just because you want them. They're gonna have to get some sort of training program and somebody's gonna have to pay them to get to the training.

And I think business leaders are starting to figure that out 'cause their investments in things, or especially around training, appear to be increasing from the survey results. Um, that said, the survey also suggests that, you know, they want internal employees to be able to do multiple jobs. Now, last time I checked, when you wind up doing multiple jobs, you do some of them well, and most of them poorly.

So it's gonna be a, an interesting set of times because I think, um, on the plus side business leaders are starting to get it on the negative side. They're still somewhat delusional. Yes.

It, it's a real issue and I agree and, and it actually brings us into a very similar survey. There are a lot of surveys around this topic and the lack of skills being a problem. So we're gonna move on to a broad wi Broad Ridge financial solutions survey, which shows, um, and this was the 2024 digital transformation report.

Um, and it shows a big gap, uh, with financial companies, um, and companies that are big investors in transformation technology and have already adopted technologies such as AI and various other technologies early they're pulling ahead of, of the other companies. Um, so when they did a little bit more research, there was only 27% of financial businesses considered leaders in innovation and technology implementation. Um, the rest are, are lagging behind for various reasons.

A big one being a skillset again, uh, and how to implement this technology effectively. So, um, again, when I speak with leaders, it's what you said. They themselves, the companies are gonna have to offer these, um, skill up opportunities and onsite, um, available training because that's, that may be the only way they're going to find the talent that they need.

Mm-Hmm. The other thing that left out at me about this survey was the leaders seemed to have, um, had more faith in their employees, right? That it seemed to be saying that they empowered those folks lower level to make decisions about technology and how to employ it.

And I think part of the issue when we talk about anything related to digital transformation is, you know, we convinced everybody that it had to be c-level led, right? And we had to have all these folks who were CEOs we're gonna drive this thing 'cause of the resistance to change factor. And I think maybe we've overestimated that.

I think there's a lot of younger employees in these organizations that know exactly what needs to be done to kind of create a digital experience. 'cause they're digital natives. I think the c-level execs want that outcome.

They just don't know exactly how to get there. The resistance is probably in the middle somewhere where you have folks that are not digital native and um, they are wedded to certain processes as they exist today. We have talked in the past how well too often, you know, somebody digitizes something and it's basically the, um, tablet version of an existing paper-based process and it doesn't really work.

So I think part of what we gotta get to now is just empowering folks at the lower levels who were tomorrow's middle managers and eventually the future CEOs to drive this. I mean, what's your perspective? Yeah, I mean, and this is all part of, you know, the agile methodologies of, you know, minimizing silos and, and, uh, giving more people responsibilities in, in different areas and everyone communicating in a good way and, uh, collaborating to get to the point they need to be.

Yeah. And I don't even know if it's a then I need to know, uh, DevOps or Agile or any of these methodologies. I think they're, you know, a nice place to start.

'cause it just gives you a cultural frame of reference. But ultimately I think it's just a matter of trust. Um, it's not like anybody's gonna go out and, you know, deliberately do something malicious or stupid just because they can.

It's important to have some guardrails around these things, but ultimately you gotta let people experiment. And the only way to really experiment is to put something out there. You can do all the things you want in the world on a proof of concept, but until it meets the real world, you'll never know for sure what you're looking at or what the challenges are and what the issues are.

You might wanna recruit some customers who are more, uh, shall we say, part of the coalition of the willing to be experimented on. But um, that's kind of where we are. And to me it just seems like we're stuck.

And whether it's in fin even in financial services where you see FinTech all the time, um, if you look at who's doing well with FinTech, it's some small startup versus typically the larger bank. I mean, uh, I won't name my bank, but you know, my bank has a decent to mediocre digital experience, but it's hardly anything to write home about. And it's not anything that I go, woo, I can deposit in a mobile check.

Awesome. Yep. That's about the level of my bank.

All right, so moving on. We're gonna completely change directions now and we're gonna talk about basketball. So, um, when it comes to the NCAA bracket picks, we have some coaches that are very irritated with the current system in place.

The, um, the, their ncaa, um, system is called net that does all their data analysis and it left out some pretty important teams and their coaches. For example, St. John's University coach Rick Patino was mystified when they were left out of the tournament.

And that's just one coach. There were several and basically went so far as to say net is fraudulent and they need to drop it. Uh, so in come some ologists who really study this stuff and they're turning to AI who help them scour through lots of data across the years and make better picks.

So what are your thoughts? Well, let's where to start. First of all, you know, Rick Pitino has been mystified about many things over the years.

So he's, uh, somewhat infamous in college basketball circles, but he, he has a point in the sense that there's not enough transparency into the process. So, um, no one knows exactly why the analytics thing recommended what it did. And, um, but still there's a selection committee, AKA people who may be relied too much on this system to make their decisions.

But you don't know because you don't exactly understand why the NCAA picks certain teams to go with certain players. Now, in the first round there were some significant upsets, right? And Kansas folks and all these other teams are kind of, uh, uh, struggling.

And I think it was Kentucky got bounced and that kind of flipped everybody out. 'cause you know, a 16th rank Oakland team beat them. And that really wasn't reflected in the outcome of the data.

But this is a human-based sport, right? It's called gambling for a reason. So if it was gonna be like the brackets are gonna be the number one seeds are always gonna win, then we can just skip to the last four games and call it even.

So I'm a little kind of like, eh, you know, sometimes I think we ask too much in the analytics, and I know analytics is all over sports today's, but um, you know, my beloved New York Yankees have more analytics than any other team, and that has not resulted in a World Series in the last decade. So I'm kind of like, you know, at some point you gotta play the game. Um, exactly.

Now this particular article, I also know the author, his name is, uh, Frank Ard, AKA, the brother. And he is also a basketball fanatic. And he and a lot of folks like him don't necessarily always believe in the analytics either.

And, and I bring this up 'cause a lot of business executives don't believe in the analytics either. They basically know where the data came from and how it was crafted. Heck, they're the ones that created the data and entered it so they know how shaky the data is.

So when someone from it comes along and says, I got this awesome analysis of what's going on with the business in their guts, they're already suspicious because they're kinda like, yeah, you know, the data is, shall we say, is ranges from inconsistent to crap. So I don't really wanna make a business decision based solely on your analytics. And people are trying to strike a balance between old fashioned human intuition and what the data allegedly says.

And these things are not always compatible with each other. And to be fair on the the, to the machines, you know, humans, a lot of times they'll sit there and say, I mean, how many times a day do you hear somebody say, my gut tells me x Well, gut telling you X is kind of like, you know, your experience kind of suggests something, but honestly is is it your gut telling you something profound or is it you know, what you had for lunch in a case of indigestion and you're just not quite up to the task of making the right intuitive decisions? So, um, it's nice to have data to fall back on, but I swear 99% of the business execs I know are shopping for data answers that support the conclusion that they already made.

And this does not help matters. And, and I know it drives the analytics people crazy 'cause they're like, but the data says x and now we have ai. Well, AI is only as good as the data that went into it in the first place.

So garbage in, garbage out. And so it's not clear to me that AI is gonna necessarily help this matter. So I mean, I'm in 19 now for near on 30 years and I love this stuff, but I'm telling you, I don't think I even make business decisions based on what the data tells me either because well I know what went into it.

Yeah, and it's just like you said, they can, they can sway the data to read however they want anyway, a lot of the times. So, um, but okay, so still in the data analysis world, we're gonna move over to a different use case scenario, which is very interesting. This was an article most recently published on digital CXO and it's about video intelligence in cities, um, helping them to come a little bit more smart cities and, uh, it's a little archaic.

Uh, a lot of cities, um, they just have someone sitting there watching all, all the, the video footage when they need to as they need to. Uh, and this is not the best way according, um, to this expert, which is, um, that you could really harness video intelligence, uh, put up video across the city and have the, the data analytics automated so that it's always, um, scraping through the video footage. And, um, and that this would help, uh, because cities have, um, increasingly operated on a lesser and lesser budget.

So as they're operating on a way smaller budget, if they utilize this smart video intelligence and um, automate the data analysis, they can make the city safer find solutions more quickly. So what are your thoughts? All right, well there's two things about this that are just flat out crazy.

So let's start with the first one. I think I remember chatting with somebody from the CIA about a, a five or six years ago and they were saying that it would take, um, the better part of a month for all the analysts at the CIA to watch five minutes of all the video that was created on the web. And so, you know, mathematically it doesn't make any sense to have people sitting there looking at a bunch of video hoping to identify some trends and analysis.

'cause the video keeps running and it keeps piling up and you'll never catch up. So it's kind of a silly endeavor in the first place. Um, secondly, the person watching the video, well, okay, there's, let's say I do see a crime in action, you know, by the time I react to the crime in action and call somebody and get somebody over there, the crime is quote unquote over.

So it's not like I'm really gonna be able to, uh, prevent a whole lot of activity. And then thirdly, you know, I grew up in the Bronx in the seventies and eighties, tough place. If there's a video camera around, the first thing that anybody who's committing a crime is gonna do is what they're gonna knock off the video camera.

So there's gonna be like, they're not that stupid where they're just gonna wave at it and go, hi, look at me. I'm about to commit a crime so that you can come arrest me later. I mean, I grant you, there are plenty of criminals who are stupid and we'll probably do something like that.

But, um, ultimately I think we need to find some analytics so that we're identifying the problem areas most, right? We really want to get to is to say, Hey, is this section of town experiencing more crime and of what kind? And um, if we have more officers on patrol here, then maybe we can prevent that.

So it's gotta be more about prevention of the, um, behavior that leads to crime. I mean, back in the eighties we had this whole, um, anti squeegee campaign in New York and it was, you know, probably, um, had some civil liberty issues attached to it, but at the end of it, it was pretty clear that, you know, if you chased down all the broken windows and small crime that you know, there's less of the larger crime because it escalates. And that's just part of what happens.

And if there's no police officers around, um, the criminal element will do what it wants to do. So, um, i I feel like this is yet another example of maybe we're asking too much in the technology, but we need it. It's just we gotta get smart about how we use it.

Absolutely. And, and I think there's ways, um, to disguise the cameras. I know there's more and more ways to disguise 'em and, uh, you know, place 'em in higher places where they can't be reached and, and then, you know, using technology to automate, like you said, figure out how to stop it before it happens and you know, populate those areas with more police officers and such.

So yeah, it's a ways to go, but I think everybody's just envisioning, you know, we're all visionaries envisioning how we can use this technology in the future, which will be great once it's a little bit better. Even now though, there's, they're selling masks that you can wear that will defeat the video recognition technology. And I don't know if you checked out the last time the arc of a, of a, um, spray can paint, but pretty much you can shoot that thing for a good, you know, dozen feet or so and pretty much take out a camera no matter how high up it is.

Very true, very true. Well, that brings us to the end of all of our digital transformation discussions for today. Do you have any last thoughts, Mike?

No. Um, I will just, you know, kind of finish up a little bit with, um, what we were doing in Paris last week at the CubeCon Plus Cloud Native Con Conference. It was, you know, heavily geek technology and mostly about, you know, think cloud native technologies from um, Kubernetes to Wasm and all kinds of buzzwords that probably a lot of folks in the digital CXO space don't fully know or appreciate.

But the big takeaway of it all is, you know, technology is marching on. We got ai, we got all kinds of new stuff coming down the pike. So if you don't have the skills to take advantage of it, I guarantee you one thing, you will be left behind, That's for sure.

Alright, well thank you all for listening to our digital CXO podcast and have a wonderful day. Bye everybody.