IT Evolution with Daniel Newman and Patrick Moorhead at ServiceNow Knowledge 2024

This is Textron tv. Hey guys, we're just after the keynote at ServiceNow Knowledge 2024 conference, and we're talking with Daniel Newman, CEO of the FU group, and we have special guest, Patrick Moorhead, CEO, chief Analyst for more insights and strategy. I was like, when I get that right.

And we're gonna talk real quick about, well, what went on in the keynote and there was a lot of points made by the CEO of ServiceNow, right? Bill, what's your first impressions, thoughts? First of all, uh, bill McDermott did what Bill McDermott does.

He brought the energy out with him, the enthusiasm, the electricity that he's brought for many, many years. Um, I knew this year was gonna be different. Now, you know, we've had the pleasure at RUM Group of working very closely with Bill McDermott.

In fact, uh, our six five summit this year, Bill's actually gonna be the keynote. So we'll be sitting down with them long form interview coming out. So everybody out there wait for that.

But, you know, today what we were looking for, what I was looking for and having been at the financial analyst day was how strong will Bill McDermott come out today and talk about the company and its compete strategy? Um, I feel like over the last few years they've been sort of coexisting with all of the enterprise software companies, but this year he's got this very strong and very intentional approach that comes out and says, look, you don't need all of this sprawl. You don't need the 12, 13, 20 different AppSec you run.

You don't need so many swivels in your chair. You can work with ServiceNow and get everything you need. That was the big thing for me walking away, was there's no more cooperation.

It's competition game on Somehow idea. I mean, they're basically making an argument for the one platform rules All. Yeah.

So to me this is, this was a hundred percent on they're going for it. And maybe this is what Daniel said, but maybe put it in a different way, but literally it's a bold and audacious plan, which is we wanna be the front end to all of your enterprise AppSec that are essentially not great, hard to use. And yes, the, the swiveling swiveling your seat back and forth.

If you ever worked at a big company out there, you know exactly what that means. But it's jockeying between multiple AppSec. So not only gonna are we gonna make your ERP system better, but more importantly your ERP connected to your CRM, your legal system, your PLM system, everything at once.

And it's bold, it's audacious. And I'm still kind of getting through, you know, what gives the company permission to do this. 'cause quite frankly, I think there's a lot of other companies that are going for it, right?

So you've got your horizontal plays, right, with your Microsoft Google. And then, you know, I think Salesforce, uh, back at the Trailblazer Dx, painted a very similar vision for the company, which by the way, enterprises need to improve not only their case in point systems, but more importantly how to activate across those systems. Bill, we know him from his days at SAP and you mentioned these backend systems.

Do you think the SAPs and the Oracles of the world are just gonna roll over here and let this happen? Or are they gonna respond? Well, a hundred percent not.

So the companies that have their enterprise AppSec are doing their best to not only improve those AppSec through things like uh, ai, but also they're expanding as well. So for instance, Salesforce Sure. CRM, but they want you to connect all of your data going through the Salesforce cloud, your ERP of data.

They want to bring either dump your data into their cloud or connect the API to that. So they're absolutely not rolling over here. One of the things that impressed me most was the tooling that they're providing to build these applications.

And they're making that accessible to your average subject matter expert, which is a great thing. But I'd love to get your thoughts on can this be too much of a good thing? 'cause now everybody and anybody can build an application.

Well, we've seen instantiations of the low-code, no-code for some time. com. Uh, it's something that I think is very near and dear to the heart of companies trying to transform, is how quickly can we get from an idea, from a business line leader to the implementation from a technologist that can then create real value?

And so you heard, uh, bill McDermott throw out the $11 trillion of economic value, the billions of, I think trillions of workflows or billions of different workflows, trillions of activities that have been automated on the ServiceNow platform. So I think getting there faster, Mike is the way. Now we've heard Jensen Wong, CEO of Nvidia, he's gotten on and said, look, you know, I know everybody told their kid, you need to learn to code.

I'm sitting up here telling you, you may not. Now, having said that, the continuum of when we go from really heavy custom code development to everybody that can speak, being able to code is not an overnight sensation. But what we do know is the law of division of innovation says the time between disruption is gonna get shorter and shorter and shorter.

And with companies that can now generatively create code. And that could be with ServiceNow, it could be what we're doing with GitHub copilot. It can be, uh, what AWS is doing.

There's different options for how this is done. But what we do know for sure, time to value needs to be shorter time that a company's product lifecycle lasts in market as meaning is shorter. So the time that they must be able to build on an now platform, create a workflow to deploy it and measure value has to be shorter.

So This has to be the path For years. And I've known you for more years than either one of us wants to count Boomer, we got X by the way. But we've been talking about, um, it is too slow to respond to the business.

Yeah. For as long as we can remember. Are we getting to the point now where maybe it and all these capabilities are able to move faster and then the business can consume?

Because it almost seems to me I can iterate and the AppSec are disposal. Yeah. So just like everything in tech that we've seen, it goes in cycles.

It's like the accordion effect, right? Where we used to just build all our own applications for the enterprise. And then you had category killers come out that said, Hey, we're actually better at this, uh, than you are.

So buy our shrink wrap software, put it on your mainframe, your mini computer, your X 86 serva. And then, uh, we got to a point where, uh, it became cloud-based and theoretically more agile and we could move faster and get enterprises up on those applications, uh, quicker. And then this whole notion, like Dan Daniel alluded to, which was, Hey, we're gonna do this even easier to customize low code, no code as opposed to a whole lot of code to be able to, uh, really get the experience that you want.

But to answer your question is yes, we're getting to the point now where it's harder for these enterprises to consume the new bits. Now, I think that enterprises have to have a strategy to where they can move more quickly because, you know, Dan called the law of diffusion. I I like to say it's not your imaginations.

Things actually are moving quicker because we have new technology working on making the technology better. And if you are, if you're enterprise and you're not in the position to be agile, to be able to do that and put, uh, enterprise applications in a mode, in a language that people can actually consume, um, you're gonna be in a tough spot. And I'm gonna tell you, I I have seen, um, you know, you look at the UI of some of these enterprise AppSec, they're, they're awful.

They literally look like they were architected 20 years ago. And I, I think, um, you know, Oracle went through their process, uh, with, uh, think it's called Redwood to modernize their applications, uh, but to get it into a modality that five generations of workers in businesses can use today. This is a bunch of left brain people making software for right brain people, and it never seems to work out.

Yeah. And then the thesis here too, you know, when it's all said and done, I just have to ask, you know, at a command line for something to do something for me, and it magically does it. Maybe that's the solution to all of this.

To me it's like a, um, it's too good to be true moment, but I, I see the architectures, I see the possibilities, generative ar ai for the first time we could actually get there. Uh, with this, What is your advice to the IT leaders and the business leaders? Because when I talk to them, they all go, generative AI is gonna be great, it's gonna be transformative.

But it seems like we're having a little challenge trying to figure out how to operationalize it, get it into the organizations and actually make it do the things we wanna do and, and to, to harness it for that matter. Yeah, I think we're on a, on a timeline that's trying to compress what we can't. So there are workflows that can be automated that we've been trying to automate using different technologies.

Remember RPA was all the rage a few years ago, then we start talking about intelligent process automation. Now what we're seeing is generative enabled workflows being automated, and you have those workflows that are very human-centric that are gonna take more time. And then you have those workflows that really were sort of pushed the button pass the baton items that worked across different applications that I think can be streamlined up very, very quickly.

I think when you're trying to look at the value creation and the time to value creation, we also need a certain amount of pragmatism. Technical debt here is no different than any other technical debt that's lived inside of our organizations. How quickly we're creating economic value and in what period of time is actually moving at quite a great rate.

Um, what I do think in the end that Bill said that if I was out there, and I'm listening to this thing, is that We don't Need a lot of applications to run our business merely for the sake of having a lot of applications. He said this very pointedly in his wrap up. He said, we have a CRM at ServiceNow.

He said, we have 24,000 employees that don't know it because they're all running on the now platform. What is he really saying is, or what he was really saying is, the way a user inside of a business wants to interact is much more like natural language in that search bar. What do I want to have done?

And across all the data, across all the applications that's small in the organization, can I get the insight by prompting the generative AI tool, uh, you know, in a natural language. And Mike in the end, that's how most knowledge workers wanna work. Um, so I think it's there to be had, I think the timeline is condensed, but I do think we are still a proof of concept phase.

Our data and future of intelligence actually says that the spend right now is proof of concept. More vendors, more partners, more implementations to test before we deploy. I think what we're gonna see is the knob turned up to 11, any music people in the room in the next 12 months.

And what we will see is these proof of concepts go to scale. It's gonna happen right before your eyes and you may not even see it. Do you think we're on the cusp of kind of reorganizing work?

And I'll ask this question 'cause we have salespeople who do something and then we hand it off to a bunch of marketing people, and then there's maybe some manufacturing folks. There's all these silos and they exist forever. But if we have AI and we can start to kind of break down those barriers, is the way a company organized gonna become kinda archaic because we just need a new way of thinking about work.

So I think what it does is it gives more lookers superpowers than ever have, right? Because your, your worker typically gets access to a very limited type of system, and now they really have superpowers when you can connect the front end to the back end, right? Uh, but even if you're a product manager and you're connecting, you know, your PLM to the, to finance, to your manufacturing system, I really think it's superpowers.

I have to say though, the one thing we haven't talked about that, I know you're the interviewer here, but we haven't talked about data, right? It's, it's finding dandy to talk about all these ca but every one of these costs application capabilities is starts with the data. If you can't get access to that data either through a data cloud, uh, an API an IPAs system, none of this is gonna work and it's dead in the water.

Oh, by the way, you then have to determine that rank and file employee. What type of results can they get? Hey, can I prompt engineer to get, you know, Dan's salary, right?

By going in another system that is enriched data together and that's something, yeah. And that, quite frankly, all our research says that one of the biggest impediments to this right now is the data conversation. Oh, by the way, and it's why Mark Benioff at Trail book Trailblazer DX is number one topic was, is data cloud.

And by the way, it's also the reason that SAP and Salesforce, some of the biggest increases in revenue are from their data cloud. 'cause you have to get your data in order to do all this fun and magical, mystical generative AI stuff. So he knows that data management is a pet be of mine.

So let me throw this out here. Okay. Data management's been a mess for decades that we have all these AppSec that are data is conflicting, the data is wrong, was entered incorrectly.

Sometimes we have multiple records that are about the same thing and different AppSec. And so do you think that my AI initiative is also gonna be my, you know, let me tuck underneath this, uh, data management cleanup initiative that the AI budget's gonna pay for. How much do you, like when your gen AI hallucinates, how much do you like when it gives you inaccurate information pulled from, you know, quarterly managed systems of record?

Well, for the brief second that it reaffirms my humanity, not much. Well, I mean, look, you know, the future of more unstructured, it's more vector. Um, it's gonna be, you know, less kind of about that traditional file and it's gonna be more about the object and the ability to, you know, use vision, use unstructured data across the web and across enterprises in masses, right?

You think about all the data that exists inside your Slack instance, um, we've got a massive problem, but I don't actually know for sure there hasn't been a lot of talk about this, Mike, but part of this technological revolution has to include an underlayer where the data has been more well managed, more well cleansed, continuously improved upon, iterated upon. And by the way, you know, the, the destruction and, and, and, and, you know, riddance of inaccurate ill-informed out of touch, out of context, data's gonna be critical because these systems, they are, there's an inextricable link between that data and the generated text or imagery or whatever you're building. Um, and we need to get there.

And so I think this is part of it, but today, and Pat and I have had this argument in many, many different vendor events, it's shocking sometimes how much we talk about the infrastructure and then how much we talk about the app app, but how little we actually talk about the data management layer, um, and how that's going to basically connect the back in the front. Last question, who's in charge of cleaning that mess up? Because historically, the IT people would look at it and say, well, I'm in charge of managing the data, but I didn't create it.

I don't really know much about it. There's a bunch of business executives creating data willy-nilly sometimes. So who's supposed to step in here and kind of bring some discipline to this?

Yeah, so the digital transformation officer typically gets saddled with connecting these two groups together. Now, the challenge with that is they're typically focused on the business transformation and may not understand the technology point of it, but, but in the end they are finding happy medium. Um, data prep is actually being improved with generative ai.

Uh, and that's something that doesn't get enough discussion, right? Which says, and by the way, my first computer class in 1984, it was garbage in, garbage out. And then I, uh, was programming on a deck VAX in 1988, and it's like garbage in.

I mean, this doesn't change, uh, what's old is new. I mean, it's always been that. I think on the good side, you can actually use generative AI because it can actually go in and look at the raw data, whether it's in a data lakehouse or something like that, and make heads or tails of this.

And hey, if you wanna stick it into an I, you know, a a a real database, it's smart enough, uh, to, to do that. But to answer your question, digital transformation officer, is the cleanup here, uh, who, who gets or somebody, uh, designated from the business unit to be the lead on this or CIO do your job right as the CEO would say and fix all this technical stuff. All right, folks, for those of you that are too young to know what a VAX or A BDB 11 is, look it off.

It's a mini computer. It's when I was talking to him back in the day. Gentlemen, thanks for coming by.

Thanks for having us, Mike. Hey, this, thanks for having me on the show. It's my first tech strong video here.

I'm really excited. It is a pleasure to have you both. Thank you all for watching this latest episode and stay tuned.

There's gonna be plenty of other episodes on text drawing tv, and by all means, check out ServiceNow knowledge 2024.