Enterprising Insights, – Leverage Data to Enable ROI from AI, Episode 28

Hello everyone. I'm Keith Kirkpatrick, research director with the Futurum Group, and I'd like to welcome you to Enterprising Insights. It's our weekly podcast that explores the latest developments in the enterprise software market and the technologies that underpin these platforms, applications, and tools.

This week I'm really happy to be joined by Robert Kramer. He's a VP and principal analyst with more insights and strategy, and Robert covers data and ERP, really anything related to data. And Robert and I crossed paths quite a bit this past spring.

So, uh, really glad he is here to join us. Uh, welcome Robert. Thank you.

Happy Friday. It's been a long week. Good couple weeks though.

It has, it has. Well, as I, as I mentioned in my open, um, you know, we've been to a bunch of events over the past few weeks and, uh, some we've attended together and some we've, we haven't crossed paths with. But I wanted to start with SAP Sapphire, which is an event that you went to Big event attended in person.

Uh, I was wondering if you could just kind of give us a brief synopsis of the events and any kind of takeaway you had. You know, it was a, it's a very interesting event. It's a, it's there basically their big event of the year.

Lots of lots of customers, and as we know, SAP is in good standings. They have great earnings and they have some key strategies around data. And surprisingly ai, everybody does.

But they're embedding AI throughout all their solutions and they're trying to improve some of their products. And some of those are rise and grow to move some of their customers off-prem, um, to off-prem from on-prem, which is a big problem. And we'll get into that with the data management discussion that we're gonna talk about.

But they had a lot of their new announcements were around that adoption to cloud. A lot of their features are only gonna be available in the cloud. So if you're on-prem, you're kind of stuck.

They have some new tools available for these integrations with their business technology platform. And they have some, some of the things that I think were really key is their new partnerships. I'm not sure if you're familiar with some of those, but with Microsoft and Google and Nvidia and, uh, Accenture.

So, and also a key acquisition with WalkMe. So everything is really around moving these customers to the cloud to take advantage of, you know, the solutions there. And also the fact that you don't want to have multiple versions, you know, all these companies having their ERP on-prem, it's impossible to support them.

So it's really centered around that and ai. So that's a long-winded answer though. No, absolutely.

You know, Robert, you mentioned a really good good point there. If we think about SAP and what they're trying to do, obviously they wanna get folks to move to their cloud-based offering, uh, because mm-Hmm. Obviously they can deliver innovations, uh, to scale there.

Uh, you know, they're, they're obviously gonna generate a lot of revenue when you're moving to, you know, in the cloud. Uh, I guess what, what is the big sort of hurdle though for organizations? Because, you know, it sounds great on paper, Hey, let's move to the cloud.

What are the big challenges involved? You know, why is there such an an effort in getting companies to move there? Well, a lot of companies am ba bastardize their system, so they have an enormous amount of customizations.

And when you have these customizations, when you migrate, those customizations don't necessarily go forward. So it's one of those things where if you move, you have to either make the changes in the new implementation in new software that you, you're gonna adopt or you have to get rid of it. And it's one of the problems that they don't see the ROI and it's a huge process of change management and data quality and getting all this, uh, information to the new system.

But SAP's gonna take the stance that they're gonna, these features that they're releasing early, gonna be available in these new versions. I don't blame 'em, but at the same time, it's creating a revenue stream for them, uh, that they're forcing these clients to go there. And it's kind of a, it's gonna be an issue as we continue down this, this way.

But at the same time, there has to be, you know, from a software provider's perspective, they can't support all these versions at the same time. But they have a, a monster of an application and you have to have an ROI and a business impact for these companies who wanna go through this program of rise, which is their cloud, um, migration offering. Right.

You know, you, you also referenced something really interesting, uh, I think it was right around the time of Sapphire that SAP announced their acquisition of WalkMe, uh, which has their adoption platform, uh mm-Hmm. Can you talk a little bit about why is that significant for SAP? Because obviously, if I understand correctly, they paid about a 45% premium based on walk, did fair price?

Well, that's a good question. We'll have to see, you know, what that does. But part of the problem that they're realizing is, you know, so about, as you look at the global enterprises, 70% of the data is still on-Prem, about 50% of all global, um, enterprise softwares are ERP and SEM.

So there's an enormous amount of, um, of money, I guess you would say, in these types of applications. So how do they get the adoption? This is part of that, that's, it's a software that could help with the change management, with the adoption of programs like RISE to move companies over from the on-prem to the cloud.

It's, it's a way to help the migration less painful. And I think they're seeing that they have a problem there and companies are not adopting this RISE program as much as I think that they think that they are. 'cause there's an enormous amount still on-premise we just discussed.

Lemme ask you a question. If you owned a manufacturing company and you had, you know, 10 facilities, you know, multi-company, multi-region multilanguage, and you have, you know, you know, customizations, are you going to move your system into the cloud unless you see some dividends that make sense? And so I think that that's the, um, architecture that has to happen behind SAP's endeavor and this, they have to show these companies that ROI.

Right. And, and you know, one of the things that you mentioned there, I I, if you have such a huge lift, there's gotta be a lot of expense around that. And if you're a manufacturer and you're a public company, you're operating on a quarter to quarter basis.

Mm-Hmm. Making that is a lot harder when you go, well, we're spending all this money and it's going to take us 12 months, 18 months, 24 months to realize ROI. Sometimes that's a hard case to make when you're evaluated on a quarterly basis.

So Yeah, good point there. Yeah. But also, do you have the people and the processes to do it?

I think that's a huge, you know, component to this. 'cause you have to have the, the talent in house and you have to have the processes to get it done. Otherwise, you could have the great software, but you can't get it implemented.

And then the data quality issue, is the data good in the on-premise system? What changes have to be made to get it to move? So this is why it's going slow.

Yeah. You know, I think that's one of the reasons why they acquired WalkMe, because their, their digital adopt platform, one of the thing that does is gives more visibility into what they actually have deployed on-Prem or perhaps in the cloud, a hybrid environment. You can't do any sort of, you know, lift and shift or whatever if you don't even know what you have.

I mean, what licenses do you have that are, are being underutilized? You know, are you having legacy applications that have been sitting out there and may contain data that, you know, is, is critical to the organization? It's really great to, to be able to get that visibility.

And I think that's one reason why they, they did pay that premium. Yeah. And I can't recall the names of the applications, but they've bought in a few other companies that are business process companies and also it, uh, portfolio management and architectural, uh, companies to help with the, this program that they're trying to get done.

So, um, they got a long way to go, but that was really the, the basis of the, um, basis of Sapphire. It wasn't eyeopening, but it was what was expected. Right, right.

I think you were mentioning, uh, Signo and, uh, lean IX were the two companies that they recently acquired. Yeah. That's great.

Yeah. No, great. Um, you know, great wrap up there.

I mean, it, it certainly, you know, I was able to join a few sessions from the plane, uh, don't, don't tell the airlines I was screaming, but, uh, uh, certainly. Very interesting. And you went to PegaWorld, correct?

I did. I just got back from PegaWorld. It was held in Vegas.

Again, lovely Las Vegas tempera 107 degrees, but, but it was a dry heat, as they say. But, uh, really interesting event because if you think of what Pega is trying to do, they're trying to carve out a niche for themselves, really focusing around, you know, optimizing workflows. Uh, because ultimately that's really what, you know, we're looking at here.

It's great to sort of say, we can use generative AI to summarize a call or generate an email, but really you only get those benefits where AI is distributed throughout the entire organization. And, and really a couple key takeaways I have from the event. Uh, you know, they have mentioned, and it was so good to hear this, that they're not just talking about generative ai because as much as that is a, you know, sort of the shiny object on the hill, they've said, yep, look, you know, you have other types of ai, predictive analytics based ai, you have decisioning, ai, um, all of those are gonna deliver a lot of benefits to the, to organizations in terms of enabling automation productivity.

And, and again, the thing they really kind of honed in on was the use of generative AI to, uh, to really sort of enable organizations to complete that digital transformation. Looking at those workflows, seeing where there's inefficiency, and then using AI to connect the dots to go, Hey, instead of going step 1, 2, 3, 4, 5, we can go step one six and whatever, and base that on any kind of data that we're getting back saying, Hey, we're gonna miss this SLA or we're, you know, doing two things twice. So I thought that was really interesting.

So their, so their main play is data and ai, right? But where are they, what's, what's their vision after that? Do they go through that?

Sure. Well, one of the things that I, that I, I wanted to also mention is they also highlighted this application is called Gen AI Blueprint. Mm-Hmm.

Now this is essentially, uh, a tool that people can use. You don't have to be a data scientist. You don't have to be a developer or an IT to say, Hey, I'm working in, let's say finance.

And currently our bill pay application is clunky. It doesn't work. Well, there are issues.

They set up this application that uses generative AI to go in and say, I wanna create this application. You put in the parameters of here's what, what you'd like, you know what data you need, you know, here are the processes you'd like to do. And it will mine not only Pega sort of repository of, of insights over the past 40 years, but it'll actually go out to the internet and try to pull in relevant information to help you create a blueprint or an architecture for an application.

You still need people to go, yes, that's good. Yes, that meets our policy. Yes, it meets regulatory, uh, concerns, but once you have that, then you can take that blueprint, put it through apps studio, and develop an application.

And the goal here is to increase productivity. That's sweet. So, you know, Alan LER said 50% productivity increase.

So we'll see if that actually happens. It's a bold claim, but I, I played around with, uh, this, uh, blueprint and, uh, I was, I was impressed. It sounds really cool.

Where, where was it at in Vegas? Was it at a nice, um, nice place? It Was at the MGM Grand, which, uh, uh, Okay.

I'll be honest, no offense to any hotel there, but, you know, all hotel rooms look the same to me. All conference rooms look the same to me, So I kind of do. Yeah, absolutely.

Uh, an interesting event. Um, you know, the other thing I wanted to bring up here is, uh, we were at an event together down in, in sunny and somewhat humid Austin, not too long ago. Long for so long.

Yeah. I, I thought, you know, so I got this new hat, you know, I mean, this is a heck of, I mean, they welcome you to Texas and, uh, this is what we get. I couldn't even check it, you know, I had to carry it and I wore it on the plane because, you know, but I don't know, what do you think?

Looks great, Texan now. There you Go. The hat I got from the security folks at TSA made me wear it through the security scanner.

I think more is a joke than anything else, but, uh, yeah. Well, what were your impressions of, of first GI give the folks a brief overview of what Zo Holics is? Any kind of takeaways you had?

Yeah, so I, it was my first Zoho and Zoho is a really a, it's a CRM and an enterprise app, you know, all in one. And, uh, you know, they have a, what about 55 different applications that you can, uh, choose from, something like that. And it just depends where you're at on the, your businesses, what you need.

And so when I went there, I was, I was really pleasantly surprised. It's a cult following. There's a lot of customers that believe in it.

Love it. It's really for companies that are, uh, small to medium size, they have a very, uh, I guess a, a cost perspective of a low entry to get customers in. And they've expanded to the enterprise section, meaning to have, um, accounting and billing and, um, I guess they have some inventory control and, uh, things of that nature to, to kind of lead into, you know, companies that are medium size, uh, vendors of like a NetSuite or Sage to kind of take some of that business.

What I got out of it, I guess at the end of the day was, I like that you can control your data and keep it under one roof. I mean, I think there's, these companies go down through growth stages. The data management is a key component, but also your technology stack.

And I have something as we get further down in this discussion today, the technology stack is a big deal because when you open yourself up, they have all these different types of software applications. There's, there's problems that will occur. So I think they, they really hit a void that I was, uh, pleasantly surprised about.

What, what was your thoughts? Yeah, I I, I would agree. I mean, if you think, like you said, Zoho sort of sweet spot, right now it's SMB to mid-market.

They do have, you know, a few, I guess, enterprise and I'll put that in air quotes clients. But really, you know, if you think about their pricing, it is geared towards smaller organizations. So they can actually do a land and expanding saying, Hey, we need a CRM.

Oh, I'm happy with the C cm. It's reasonably, it works pretty well. Hey, I'd like to pull in my e-commerce solution.

I'd like to pull in my, uh, my billing solution. Uh, to your point, I think for these smaller organizations, they, they need to be worried about data management, data governance because of the fact that, you know, they don't have these massive staff, you know, resources to handle that, to pull in other consultants, right. Having that on a single platform.

And then of course, the other thing that, that Zoho, you know, certainly wanted us to, to reflect is that, you know, while they do have this centralized platform, they do have integrations with other things. 'cause let's face it, it's very, it's few and far between the, any organization is, you know, uh, a true single platform vendor. Um, the other thing I'd I'd like to mention there that's really interesting is they are a privately held company.

They had a whole presentation really talking about their core values, all of which were really, you know, allowable. They haven't fired anyone in gosh knows how many years. Uh, they, they take an ethical approach to where they actually locate their o their offices.

Mm-Hmm. Tend to go second and third tier markets, hire locally, and then pay them a wage, uh, people wage that, you know, is fair. And then, you know, they don't ask people to move to Silicon Valley or to New York or wherever.

So it's a very interesting company. I, the, the only question I had after all of this is, uh, you know, what, what is the, you know, potential downside, not everything can be rosy, but to date, I'm not sure. I think the only thing I would say is that, you know, as they grow, it might be hard to kind of maintain those values.

Yeah. Yeah. I, I think so.

'cause, you know, but your, your employees are your biggest assets and you empower them, you'll get more out of them. And I think that's the mantra for Zoho. And it's, um, the business model is unique, but good.

And also the low entry point. 'cause once companies put all their data into an application, they're not gonna wanna really move it unless they, there's a compelling, you know, um, case for that. Right?

There has to be a re a business value for them to do that. Otherwise they're gonna stay where they're at because it's time consuming. Your time is worth money.

So, you know, when companies say How much did it costs? I can't just say, Hey, it costs whatever you put on a piece of paper. And, you know, from a financial where you move money, it has to be what it costs physically for those people to actually do the work.

So if it takes this amount of man hours or, you know, conversations, even this discussion here costs out, you know, money because of the fact that we're talking. So I think that it's a, it's something that Zoho has figured out how to maximize that certain small to medium business. So kudos to them.

Yeah. You know, the other thing I think that's important to mention about them, and, and really we could say the same thing about SAP about Pega is obviously AI is a focus. Uh, everyone is rolling out their assistant.

Some of 'em are called copilots, probably more than I would like to, uh, revert to them. Yeah. But, uh, others are, you know, Pega has their gen, ai, AI buddy, uh, what have you.

I, I'm curious to get your impression on all of these sort of as gen AI assistance, are they going to become essentially table states pretty equivalent in terms of overall functionality? What's your sense? You know, I think that they're only gonna be successful if the data is there to use, you know, to be utilized by ai.

So I think companies will fail if they don't have a successful data management strategy, because the data is the key to the success of ai. And if they have it put into place, I think it'll be very good. But at the same time, I'm not sure that the most companies are focused on that data management strategy.

They're looking at these demo, these demos in this, these really nice, it's like going shopping and you walk through by a window and it looks good. But, you know, I'm not, my physique doesn't really lend to putting those clothes on. It won't look good on me, but it looks good there.

I think it, not the best analogy, but at the same time, how is it gonna work? What are the keys? I don't think the vendors are, are really telling their, uh, customers what they need to have in place to have a successful AI program.

And that means like, you know, the processes, again, the, you know, the people and putting that in place to maximize and what does a data set look like? What's the connection to your ERP systems? What other data sets are are necessary to maintain that equality?

And then I get my AI strategy, um, to be successful. What, what's your thoughts? Yeah, I, I would agree with that, and I would, I would say that the problem is that, as you mentioned, it's very appealing and very interesting to talk about generative AI and all the crazy things that it can do.

When you start talking about data management, data governance, that's where it, it doesn't sound as sexy, but it's actually even more important. And I would love to get your thoughts. Uh, you went to another event, in fact, you just got back from Databricks.

I'm curious to see if there was any discussion about these sort of more fundamental topics around data. Yeah, so the, you know, they have a data intelligence platform, and theirs is all about data and ai. And, um, they have a very interesting story.

And what the intensity of this, um, event was, was, was actually fabulous. I was very impressed. So they're kind of that middle layer.

So if you have all these different applications and you need a platform to put 'em, and just the data, data does not sit with them, it sits where it resides, then you have a chance to put together the intelligence around all that data and the applications that the data is coming from. An example is, I talked to, um, and this is a wild story, one of the major top five airports in the country. And, uh, I sat down with them to see what their take is on Databricks and how they use 'em.

They have about 250 different applications, and none of them talk to each other. And this is a major airport. And I'm like, well, who's the, who put that together?

So anyway, data is, has put that together. They have a dashboard that puts everything into a, um, a nice, you know, gift wrap dashboard. Now they can understand the, um, the passenger journey.

You know, they can understand, you know, the, the parking, the traffic going into the airport, the, um, you know, what flights are on time, what, what are not, you know, what, um, you know, I guess, um, terminals are crowded, what baggage claims, you know, on and on and on information about the, the actual person that's traveling. So the traveler's journey is a big deal. And now they can really make adjustments.

And if I told you that airport, which I will behind the scenes, it, it still runs pretty well. But at the same time, Databricks is a chance to aggregate data and AI together to, to give this intelligence that I think that that middle layer that is gonna be very popular, which already is, it's a, I think it's about a 45 billion company, something like that. But, um, and, and this is a, this is one of those mainstreams, you know, snowflake does the same thing.

Another company called Cloudera does it as well. So these are gonna be more of a way to put the glue that's needed, um, the gap between, you know, all these ERP systems and these, uh, SaaS applications. Yeah.

You know, I'm glad you raised that issue because I think, you know, when we look at it, we step back and go, why are there, you know, 45 different, you know, ERP systems? A lot of it is due to, you know, either acquisitions or, you know, even just, I mean, you look back in the pandemic a few years ago, sometimes companies had to stand up things very, very quickly just to get something done. Now that they've been able to take a breather, they go, oh my gosh, I have data here, data there, data everywhere.

It's not talking, we're not getting insights. We're not able to look at things holistically and then apply AI and really automate a lot of these processes that, that, you know, it's 2024, you know, we should be at least halfway to the Jetsons, you know, by now. So We should, you know, at the same time, I think ERP companies are starting to modernize, meaning they're, they're being more flexible, they're scalable, they're not as traditional on-prem and limited features.

So they're taking advantage of the technology, like the AI that we've been talking about. At the same time, you have this middle layer, or you have intelligence platforms that are allowing to put different systems together. Um, I think the one thing that needs to happen is companies need to evaluate before they just grab another SaaS application and add it to their technology stack.

Because all it is, is it confuses everyone. And then how does the data get there? Who owns that responsibility?

And, and that's really one of these caveats that I think is a growing problem and a headache, you know, for, uh, you know, these technology officers. And probably more to come chief data officers, because how the, how are you going to manage all this data and where it goes and why do you need it? And so I think these intelligence platforms will help reduce that.

At the same time, the modernization of the ERPs will bring that as well. But, um, it's a really, it's a big subject. 'cause I, when I was talking to the SAP folks, you know, I said, who owns that responsibility for the data?

And they, they don't necessarily think they do. They just, you know, if you use our system, here's the data and then, you know, we'll help with these programs, but at the same time, the vendor who it's going to owns that problem. And I think that that's a gray area right now.

What's your thoughts on that? Absolutely. We, we've talked about this, uh, you know, at different events, you know, over drinks at the bar.

And it's very, uh, it's a, it's a problem because again, you know, if you think about it from the vendor perspective, their goal is to provide a particular offering, you know, to help them do a specific thing. And I think a lot of times the, the lines between who owns what data, who owns, you know, the responsibility for vetting it, making sure it's clean, making sure that it's usable. You're run into this, this whole issue where, you know, nobody wants to take on that responsibility because it's huge.

Um, but I think that ultimately there will be a need for someone to come in and take that responsibility because you're now, you're seeing organizations rely on data that is outside of their organization, uh, what I used to call it, like sort of ambient data where it's like, Hey, I'm going to the airport, but also I want to incorporate things like traffic data or weather data or whatever else to really provide that customer with a full picture of what's going on. But if we don't know where that's coming from, or the validity or, or going back, you know, and that's, that's kind of a, you know, not a great example, but you kinda get the idea. It, they, they really aren't trying to federate data from a lot of different sources, Right?

Right. But the responsibility has to be owned, and then the customer, they're not, they may or may not be savvy enough. And I think it poses a, a tremendous problem problem.

And then that's part of the issue where we go forward with, is data management successful? Is your AI gonna be successful? And it could be the fall of AI at certain companies because of this whole process that we're talking about, the data's not moving over correctly.

There's not proper, um, you know, governance in place to get it all done. Right? And then there's no change management to, uh, make sure it's, um, it's processed correctly.

Yeah, this all sounds like, uh, like everything, it does go back to becoming a people problem in terms of making sure that policies, people align with the technology. So Yeah. Yeah, Yeah.

But, uh, we could, we could go on for hours and days and weeks and months and years about this, but we do need to wrap up. And, and as you know, Robert, one of the, you know, one of the favorite things I like to do at the end of the show is, you know, provide an opportunity for you to rent or rave about something in the market, perhaps something in your travels. Uh, so I will, uh, kick it to you first.

Do you have a rent or a rave for me this week? Well, let's think about that. I think, you know, I'm gonna rant a little bit about, um, I like Databricks.

I, I like the way that their intelligence platform gives data a chance to be better. And it was really, it was an eye-opening, um, event. They really did a great job, um, from just the, the process of, um, taking care of us at, you know, from an analyst perspective, allowing us to meet the right executives, allowing us to, to hear the things that we needed to hear and explaining, you know, how they're gonna influence the market and change the market.

And I think that that's a big topic today because data, um, it's not just about the features, it's about the functionality and the ROI and how the business impact is affecting these, uh, customers. So that was really something special. But there's a lot of, there's a few other companies that do the same thing.

And, um, I like that space and I like also the companies that help with these integrations. Um, like a super IPA with a software ag and a few other ones. So I like that middle layer.

I like to, uh, rank about that a little bit, um, in a positive, uh, way. So I guess, how about you? Yeah, yep.

Sorry, you, I haven't been on the show a lot, you know, I was confused. I had the hat on and, you know, now I'm, uh, I, I, um, got home late two in the morning last night from, uh, San Francisco. So I, that's a rave and, uh, give kudos to Databricks for a well done job.

Awesome. Awesome. And I'll also, uh, for some reason I'm in a good mood, I'll rave about something as well.

Uh, being at Pegasystems, one of the really interesting things was we did a sort of a pre-briefing session for press analysts. And their CTO of Don German actually came out and said, yes, we have a chat bot. We have an assistant to help you do things with generative ai, but we understand that that will become table stakes.

We do not believe that to be the reason that we are winning in the market of losing in the market. Um, to me it was refreshing to hear that candor that, look, AI in of itself is not gonna be a differentiator. Everybody's gonna have it.

Everyone's gonna have their own version of a chat bot. Everyone's gonna have their own version of an assistant to help a call center agent. What really is going to come down to it is how can an organization help your, how can a vendor help an organization manage its data to get the most out of those tools?

How can an organization leverage generative AI to really look at the processes and workflows that underlie or underpin everything else in the organization? So it was great to hear that, uh, you know, 'cause I, we, we both go to a lot of events and everyone says we have the best this, you know, my chat bot, chat bot, you know, all of that kind of stuff. And, uh, it's just really nice to see an organization realize that hey, or admit that, hey, we have good technology, we like it, we wouldn't develop it otherwise, but in the end, that's not how we're gonna compete and win.

Yeah. One question about that. So one of the things that I did see is, um, at Databricks they talked a lot about collaboration.

That to get rid of the keyboards to collaborate to that, that will never go away. But the combination of the data, the AI, and the collaboration is really the key. And I haven't heard a lot of companies talk about how important collaboration is, they talk about it, but the key to, to success, I guess that goes back into the processes and the people was that talked about at, uh, Pega Systems.

Yeah, a a absolutely. I mean, the collaboration is, is gonna be the key for everything. Because if you think about how in the past if you were to develop an application, your collaboration was, well, let me request it from it, it comes back and they give you something, you go, this does not do what I want to do.

You go back and forth and back and forth, right? Time wasting, wasting. Now by using an app like, uh, blueprint, you're able to collaborate in real time with who all, whoever the stakeholders are, who before, during the planning process.

So when it is ready to be developed, you have sort of a finished plan. You save time, you save money, effort, everyone gets their what they want and hopefully, you know, you don't gotta do it again. So, absolutely thank Sounds good.

Alright, well, Robert, uh, I, I see by the clock on the wall, that's a all the time we have today. So I want to thank you so much as always for joining me here on Enterprise. Thank you.

Absolutely pleasure. And to everyone, to everyone out there, uh, I'll be back again next week to report on all the happenings within the enterprise software market. So, uh, for Enterprise Insights, I've mean Keith Kirkpatrick.

Thanks a lot and have a great week.