We are live for episode 31 of the Hot Desk Podcast with Melody Brue and Robert Kramer for a rundown of what’s up this week in enterprise apps, collab, and data security.
Watch the full episode here:
Listen to the audio here:
1:57 SAP Q2 2024 Earnings
6:57 IBM Q2 2024 Earnings
12:15 Alphabet (GOOG/GOOGL) Earnings
20:38 Salesforce & Workday Partnership
27:30 AI Journey in CRMs
SAP Q2 2024 Earnings
IBM Q2 2024 Earnings
Alphabet (GOOG/GOOGL) Earnings
Salesforce & Workday Partnership
https://www.salesforce.com/news/press-releases/2024/07/24/workday-employee-service-agent/
AI Journey in CRMs
https://www.forbes.com/sites/moorinsights/2024/07/24/3-reasons-to-start-an-ai-journey-in-your-crm/
Disclaimer: This show is for information and entertainment purposes only. While we will discuss publicly traded companies on this show. The contents of this show should not be taken as investment advice.
Transcript:
Melody Brue: Welcome to this week’s edition of Moor Insights & Strategy Hot Desk Podcast. I am Melody Brue. I am joined here by Robert Kramer and Jason Andersen. How are you guys doing?
Robert Kramer: Doing great.
Melody Brue: Excellent.
Jason Andersen: Doing wonderful.
Melody Brue: Well, I’m happy to have both of you here while Robert, you’re here all the time. But Jason has been a guest with us before and joining us again this week because we have a lot of good stuff to talk about. This week, we are going to be talking about SAP earnings. Actually, it’s been a whole week of earnings. So we have SAP, IBM, Alphabet, and then we’re also going to be talking about Salesforce and Workday partnership. And then we have Jason’s first published article, although not really because you contributed to a lot of other things. Jason’s first solo published article in Forbes, an AI journey Starting Out In CRM, and we’ll get to that.
But a little bit about the Hot Desk Podcast if you are new here. First of all, I don’t know why you’re new here, why you haven’t been here before, but we talk about so many things. All of the tools, trends, and trajectories in People Tech, in ERP, which we’ll be talking about a lot today. Enterprise data, modern work, HCM, CX, lots of other things. When Jason comes on, we talk about developer tools and other things, and then of course, the glue that holds all of it together, which is data. One disclaimer, this show is for information and entertainment purposes only. We will, especially this week, discuss publicly traded companies and its content should not be taken as investment advice. So given that, you guys ready for some earnings palooza?
Robert Kramer: Let’s do it.
Melody Brue: All right. So we’ll start out with SAP. So SAP released its Q2 earnings, Q2 of 2024 obviously earnings this week on Monday, surpassed analysts expectations, both top and bottom line. Big thing here I think is it reported a ton of growth in cloud and cloud ERP segments, and its first double digit revenue increase in five years. So couple big things I think obviously that led to this. AI played a huge role in the ERP and their line of business deals. And when they say line of business deals, that’s like their business functions within the organization, like asset management or R&D as opposed to enterprise-wide agreements. Any comment on some of the numbers, big increase in revenue?
Robert Kramer: Yeah. Well, they’re embedding AI through the platform and also recently introduced into RISE, which I think will bring those numbers or support those numbers. Jason, you have to tell me what you think, but the RISE Programme is such a big deal because there’s so many clients sitting in that whole grouping, 25,000 total. I think they’ve gotten 6,000 to convert to the cloud, so they see that as a really strong revenue coming forward.
Jason Andersen: Yeah. I think there’s a couple pieces to that, Robert. The first is that they’ve added more people to help the customers make the move. So there’s more hands-on help. Additionally, now with AI embedded in the tool set, generative AI is really good at migrations. It’s good at code migrations, it’s good at language and documentation migrations. So all these customers who may have felt stuck before can now actually leverage this technology to help them move forward. And I think they’re starting to see that there’s some real potential there. So I do think that that’s going to help them convert. And SAP has a huge incentive. They pointed to some numbers where they’re saying that once a customer converts, the revenue opportunity goes up by 2 to 3X because now the customer is in their cloud, they’re able to upsell and cross-sell them more services so that ERP customer may in fact someday become a concurrent customer, for example, or something like that. So they have a real incentive to get the customer there, and it looks like now maybe they’re finally in a position to lower the bar, so to speak, on helping them to do that with RISE.
Robert Kramer: And I also think there’s a way for those customers that are not going to go to the cloud to do a two-tiered approach where they have their core infrastructure that will never go from on-premise to some of the second-tier modules that they can take advantage of those modernization applications that are in the cloud. So that still brings pretty substantial revenue from that perspective. And then the upsell, like you said, to concur some of the sales and expense modules that are out there. So good day for SAP.
Jason Andersen: I liked it because they use customer names in an investor pitch, which doesn’t always happen.
Robert Kramer: Good point.
Melody Brue: Yeah. I was going to say there were a couple of things that we called out in the article after SAP Sapphire, that was one of them that they used some customer names. They gave some more of a customer-centric narrative. One thing that they didn’t highlight, which SAP typically does is their sustainability efforts. They did, however, just a day after or two days after it’s been in the last couple of days, release their DEI report. And it doesn’t include all of their sustainability efforts. But one thing that it did include, which I was really impressed with, was the accessibility of their technologies.
So I think in the past year or so, there’s been this whole DEI backlash because people look at it as people somehow getting some unfair advantage. What I love that SAP is doing with DEI is they’re making their technology accessible to differently abled people. That was just for me, something that I saw and went very cool. That’s the DEI that the world wants to see. The DEI haters need to be exposed to that. It’s not just about somehow different people getting in some people’s minds or Elon Musk’s mind, some sort of unfair advantage. So if we’re all done with that, I’ll end with that and we can move on to IBM earnings from this week. And Jason, you had quite a lot on… Actually no, Robert, I’m wrong here.
Robert Kramer: We can both trade off on this and chime in, but they had a really successful second quarter. You have to say what you think Jason, but geared towards AI and their cloud strategies. Also, their acquisitions of HashiCorp and also some other ones like Software AG, which I’ve been covering for a long time and some of their new partnerships. But what I like about them is first of all, they’re completely set up from a diversity standpoint where they have their software, their consulting, and their infrastructure. And those three different segments really make up a substantial amount that it diverses the company where it’s not all lopsided. Mel and I have covered lots on X, the data platform and some of the neat things they’re doing there with AI and how they’re really set up and they’re buying technologies like the Software AG to prepare themselves. And Jason, this is really something that you talked about for what’s coming up down the road because a lot of these companies, what they’re doing from an acquisition standpoint and investing their monies in AI and other areas are to set themselves up for the next generation of technologies. But what I see is IBM had a really strong quarter.
Jason Andersen: Yeah. I think it’s funny given 2024 version of a strong quarter, but they did have a relatively strong quarter in terms of beating the estimates, and actually raising some of the expectations around cash and things like that. So they did a really nice job on the financial side of it. But two things really stuck out with me. On the technology side, I think the first one was they’re really starting to get a great articulation, I should say, around software-based automation and something that hasn’t shown up a lot in my research yet, but I’ve been talking with a few companies about where I call it the digital supply chain. So how is it that you start out with say, an open source component, get it all the way out to production and maintain it and support it so the entire goes beyond continuous integration development into the whole financial picture and things like that. IBM is really painting a vision to that and it’s pretty impressive. And they’re making acquisitions like Apache and starting to do deeper integration with Ansible. So they’re doing neat things there.
The other thing that really stuck out is that IBM is very much a services business. It’s been a services business for a long time, and they said that they’ve generated about 2 billion of revenue in generative AI related work. That’s product and or service work since they started doing GenAI. So they didn’t give a date. So we don’t know if that’s 3 years ago, 2 years ago, year ago, I don’t know, but they said it was $2 billion. And you go, “Okay. Well, that’s interesting.” But what was very interesting was 75% of that revenue is services. And when you consider, if you’re a typical software company, it might not be that impressive if you’re doing more service than software, but in IBM’s case, the services often a leading indicator of future sales for products. That’s just how their business model works.
So the fact that they’ve done so much service, a billion and a half dollars of generative AI services, that means probably down the road there’s some real potential for them to sell some products as well, including those automation products I mentioned earlier, but it could also be Watsonx or other things. So I do think that in addition to having a solid hit this quarter, as Robert pointed out, there are some long-term things they’ve put in place to continue and sustain their presence and their value.
Melody Brue: I think an interesting thing with IBM in recent years is that they really are four different companies, and a lot of people have been somewhat confused as to what they do. And I think they have, honestly, they’ve done a good job recently of clarifying that with their partnerships, with things like their sports technology group, which actually exposes their technology to the world, differentiating what those different companies do and explaining that better. So I think that helps people from an understanding standpoint because the company has evolved quite a bit.
Jason Andersen: Very much
Melody Brue: It’s easy for us to tell the story when the story is a little bit clearer. And I do think the partnerships with Microsoft, they have these centers of excellence or these places where you can actually go and interact with the technology. I think that those types of things really help to tell stories. When we were even talking about with SAP, when you can tell a more customer-centric narrative, it helps. And I think people sometimes get this stuck in their mind that every buyer is an IT buyer. Not everybody purchasing software or products is actually an IT buyer. And I think IBM has really come a long way in telling that story from that perspective, which we can move on to Google earnings because there are certainly non-IT buyers there.
Jason Andersen: Yeah. I’ll go first. I guess Google was interesting because they too have multiple businesses and I think they did a fairly good job, actually probably better than fairly, did a really good job this week of spelling out the metrics for each of those businesses. The standout for me was how well their cloud business is performing, which is an analog to what I would call their enterprise-facing business. It’s now a $10 billion per quarter run rate. They’re generating 1.2 billion in profit. So that was a huge milestone for them this quarter. They were very excited about it.
They also had a lot to say about the search business. And if you think about two or three years ago when you started to see generative AI begin to show up in the mainstream discussion, there was a lot of talk about that generative AI would kill these search companies. And in fact, not just Alphabet and Google, but I mean there’s other search companies out there even say Microsoft, who really turned this technology in its favor to make a much more compelling offering. And that is showing with the numbers.
The one area that with Google that wasn’t a big surprise was their streaming YouTube business isn’t doing as great as the other businesses right now, and that’s the more consumer-facing stuff isn’t doing quite as well, which is the inverse of what you’re seeing in the market where consumer is doing better than enterprise spend. But nonetheless, their diversification is really helping them out. Like I said, the cloud thing really stood out because they were also able to talk to the power of what they have and what people can do.
For instance, they could support more the biggest prompt window for AGI use cases, that it sounds really nerdy, but the truth is that if you’re really trying to solve a massive problem using artificial intelligence, the Gemini model is probably where you’re going to look first because you can actually put more information into the model to get it to understand it and bring it back to you, whether that’s healthcare research or something like that. So I thought that was a pretty powerful story as well, that they’ve really taken this next shift in technology to heart and they’re really putting it to work for them, which was pretty impressive.
Melody Brue: Yeah. Are you using Gemini at all? Have you been playing-
Jason Andersen: I’ve been playing with Gemini. To be honest, I’ve been dating a lot of models lately.
Robert Kramer: That’s a pretty good line. I like that.
Jason Andersen: Yeah. You like that? It’s pretty good. You can use it whenever you want.
Robert Kramer: I might.
Jason Andersen: I’ve had mixed results depending on what I’m doing with each, to be perfectly frank, I probably had the most consistent… I haven’t had the most consistent experience of Gemini, but when it clicks, it clicks really well. And when it’s embedded in search and when I’m using it for search, it’s doing a great job. That particular use case, it seems like they’ve really nailed that one where when I’m using the traditional Google approach and it gives you that new window on the screen, that’s pretty great stuff.
Melody Brue: Yeah. That’s what I was going to say is, it may not be consistently across the board every single time, but there are times, and I do believe that you really do. Not everybody has to be a totally a prompt engineer, but you do have to know how to ask the question and you have to maybe ask a couple of times. But sometimes, I just find that I get phenomenal results from Gemini. I’m actually really impressed when I feed it all of the stuff that I want it to digest, and then I ask it the right questions, I feel like the results are getting better and better, and this has just been over, I would say just over the last month. I mean, I would say it’s a pretty drastic improvement. I’m really liking it. I think you’re right in terms of it search changing. I think Pat mentioned recently that he was using perplexity for the majority of his search. I think a lot of people are using that. I was using Bing for a while and I really like the citations in Bing. I think that-
Jason Andersen: Yeah. And now a lot of people are really excited about what Anthropic doing in Claude is doing right now. So it’s just an arms race. And it’s interesting because even Google brought this up was that now you’ve gotten to a certain point of let’s call it competency or some degree of parity across. So now they’re all comparing what it costs. So that’s generally a sign of maturity is when they start saying, “Yeah. But I can do it cheaper.” And they certainly brought up that point on the investor call was how much the combination of their chipset plus their model together is going to drive down costs, and that ultimately is going to help them continue to drive profit out of the business.
Melody Brue: So I mean, we got off topic of the earnings. One question for you on the Google earnings is they really talked a lot about how much hiring they’re going to have to do. Is that a concern do you think for investors? Because I think that one, there is a pretty big talent gap right now, and the competition for the really skilled AI talent is going to be steep and costly.
Jason Andersen: Yeah. I think with Alphabet specifically, it was interesting because they essentially have established what I’ll call a baseline on capital spend, and capital spend is the data centers and the servers and the GPUs and everything to build out. So they’re basically flattening that out. So they seem to be comfortable with it where they’re at for that. I don’t know if people, the workload has to catch up or what. I don’t know why they’re doing it that way, but that’s what they said. But to your point is that they are not necessarily taking the same type of actions with expense, but flip side was SAP did talk about it where they’ve automated about what 30 processes already in their business, and it’s helping them not hire.
I think it comes down to that. If you’re building out these models, you still have to spend a lot of money to stay in the race. But if you have a smaller model or a no model at all, which would be a smaller model, would be IBM and SAP strategy with their models that are smaller and they’re not as general purpose, or you’re even AWS with no model, you’re just using other people’s models. It really does make a difference because the people who are leveraging models and using AI internally are suggesting slower hiring, which is probably good for investors to hear, but bad for tech employees to hear. So that stinks, but Google is still putting money into, you’re right into people to try to keep up with the Lammas and Anthropics and ChatGPTs and everybody else. So that’s an area of rapid hiring and skills, and that’s going to be a problem for those companies. You’re right.
Melody Brue: Anything to add before we move on to the next thing, Robert?
Robert Kramer: No, I’m in agreement with you guys. I was actually thinking about the YouTube comment that they said that it was not doing well, but I thought I read that it was the most watched station on the internet still. So with that, I thought it was surprising with the money not being there.
Jason Andersen: I think it comes down to just the cost of streaming and its subscriber growth. I think there’s pressure on… I think it’s a revenue problem, not necessarily a watching problem. I mean, people like me who don’t pay for YouTube TV, I’m costing them money. So I can watch Mr. Beast videos and Morgan Eckroth make me really nice looking coffee drinks and everybody else on YouTube.
Robert Kramer: There you go.
Melody Brue: Well, it is definitely not a watching problem in my house, but I have a whole bunch of teenagers, so lots of TVs here but anyway. Actually, this is our shift to the next topic, which is Salesforce and Workday is a good segue in as we were talking about human capital needs. Salesforce and Workday this week announced a partnership with AI, they’re wanting to transform the employee experience and it’s built on Salesforce’s agent force platform with Einstein AI combined with Workday’s platform and Workday AI. So they’re throwing all the AI in, but really what this means is that they’ll have access to a shared data foundation combining Workday’s financial and HR data with Salesforce CRM data. So employees can from day one, ask questions about payroll benefits, company policies, ask the training questions, everything. So it’s really basically an onboarding tool, but then also an ongoing tool for the employee experience. I think one of the critical human connection things remains that you have to have a human in the loop, and especially for these more complex issues, and the AI agent will escalate to a human agent, and I think that’s super important.
Also, within this partnership, they have a further integration with Slack so that employees can interact with their Workday data just within Slack. They can ask questions and all that already without having to leave Slack to do that. So if you’re using Slack, obviously. So I think this isn’t surprising, I would say, but I do think it’s one of the use cases, and we will get down to CRM next, where it makes a whole lot of sense to have AI in… We’re talking about two different places here, in CRM and in HR, where it really works very well to pull the data and regurgitate, and you don’t have… Well, I guess I shouldn’t say you don’t have. It eliminates some of the risk of the human error. Training is by the book. Policies are by the book. Everything is according to what the model is trained on.
So I just do think that companies need to be aware of the human element of this because if your first day on the job is being onboarded by an AI assistant, that may not be the most welcoming first day. So I think there’s got to be some balance of this, of what we were talking about before of automation and helping with expense and all of that, but also making people feel like people and part of a team. But I guess there’s some of that, that occurs in Slack. So the integration in Slack is actually helpful for that, because that’s a place where you interact with your team and all of that. So I think it’s definitely, again, not surprising, a sign of things to come, I believe.
Robert Kramer: Yeah. Don’t you think that one of the things within HR of companies is that they don’t give the employees enough attention? I mean, I feel like employees always are looking for information that work for these gigantic companies. So does this help them maybe from an efficiency standpoint, but then hurt them, it pushes them back from that human touch a little bit more? And then, does it also complicate the stack or the technology stacks of Workday and Salesforce or more Workday? Because it seems that the data element here is a big thing and that the data is off, then this isn’t really an efficient play. So the complication worries me, but just wanting to see that human touch, because that’s what human resources is.
Melody Brue: It is but there’s so much that goes into this, especially with these distributed workforces where the compliance is so important where you have employees in different countries, in different states, and the laws are different, and a human may take one longer and may make more mistakes. So when the HR groups have these types of resources, they’re freed up to actually have the more human interactions. But if you look at something like what SAP is doing in success factors with Jewel and Microsoft Copilot, they’re actually using the joint AI to find up-skilling opportunities. This is something that in a big company, an HR person isn’t necessarily going to pick out an employee amongst thousands of employees and say, “Hey, you might be a fit for this job.”
So it’s a real benefit I think, to both the company and the employee if used correctly. And I’ve spoken to tons of HR business managers or business partners, and for them to actually get back that time to do the stuff, they don’t want to do payroll and compliance. That’s just part of the job. They want to develop people. That’s why they have the job, typically, most of the time.
Jason Andersen: You’re starting to see the next door. This is a sign of a next door type of AI use case, which actually makes things better versus just makes things faster. As somebody who worked at a company that tried to deploy a agent-based HR system, and it wasn’t successful, it was because there was no value to it. It was completely just a cost-cutting measure and it didn’t make anything better. So it made people upset, and people would just refuse to use it, and they kept calling their favorite person in HR and it just blew up in their face. So if you find ways to add value where, hey, for this class of questions that are easy, do this and for this other stuff, now we can actually become more of a proactive organization than a reactive. That’s a positive thing. So you have to add some value by bringing in the technology, or if you don’t, it’s over.
Melody Brue: Well, once again, good segue into places to start your AI journey.
Jason Andersen: Yeah. We started to see a lot of noise, like I said, these second order use cases where companies are starting to do more interesting things with AI than just have it churn out a piece of a paragraph of marketing content or something. And it started to really show up in some of the announcements coming from different companies in the CRM space. So I dug in a bit, and as a matter of fact, just last night my first solo piece on Forbes was put up about why CRM solutions may be an ideal place to start for an enterprise to start an AI journey. And it comes down to three big reasons, and I’ll just summarize. There’s the fact that there’s a lot of data in those systems that can be tapped into. There’s a huge process automation opportunity because especially in the go-to-market space, because so many routes to market and there’s so many ways to create demand, and there’s so many ways to do things like email marketing or account-based market, so many techniques that can be deployed and quite frankly, go-to-market teams are pretty strapped. They don’t have necessarily the resources to try everything.
And then lastly if it’s revenue-based, it’s going to have higher visibility in the organization, which means that if it’s successful, more investment will come. It’s one thing for you to go to a leader or an executive in a company and say, “Hey, I can get you an ROI of this by cutting out these costs with AI. My developers are more productive. I can save money on my development operation costs.” Whereas if I could say, “This is a way to help us make more money than that.” That gets a lot more interest and a lot more investment. So those three reasons suggest that.
Now it’s funny, there’s another piece, believe it or not, a follow-on piece for me about this very topic because yesterday, Salesforce is actually now doing a tour around the world called AI Now, and it’s essentially an all-day lab session to start to use AI in a Salesforce context. And I’m going to have a piece coming out, it’s an editorial right now, it should be coming out any day. But what I wanted to point out about that was besides the fact that it was a great event and you had a room full of Salesforce admins figuring out actually how to use AI in their environment. The first part that was super cool was actually they could have called it the Robert section because it was two plus hours on how to get your data house in order using Salesforce. They have a new product coming out called Data Cloud. It’s coming out in the fourth calendar quarter and it’s in Sandbox now, and it is basically a tool to help unify and transform data such that AI can use it. So it was funny that AI Now it’s really AI after three hours of training on how to get the data right.
Melody Brue: AI
Jason Andersen: So it didn’t work as good, but the truth was is that it really did echo a lot of what we’ve been saying for a long time about how to get started with AI in a very practical user-oriented sense. And it was cool because you got to see people who are used to using the CRM system now use these new tools and try to figure it out. And I will say that as the day went on, the projects got harder and the hands went up more and there was a lot more interaction. So the data part people got, but when you started to get into, okay, how do I build a workflow that leverages an LLM, all of a sudden you see 20 hands in the room shoot up. So it was fun to go to an event where people are actually really hammering out and trying out code versus just some of the big vendor events we go to. But it was very telling in the sense of that, I think not only was it nice to see validation that Salesforce also thinks CRMs are a great place to start an AI journey, but it was also great to see it actually in use and to see where it’s going to maybe get some initial traction versus where it might take a little while to develop more.
Melody Brue: Awesome.
Robert Kramer: Sounds good. I actually think you’re spot on around AI and CRMs because the marketing departments, the more edge they can get to be more efficient because we spend so much time doing manual functions within marketing, and I do believe marketing is a big asset for companies, but it’s sought out as being spent. So the more efficient they can get, the more glory they can get at the same time, and this is a great segment on CRMs.
Jason Andersen: Yeah. If there’s anything I could say, they actually had some very nice use cases. I think could, and I say this in my piece, is that they could have done a little bit of a better job of connecting that to the business value, but the best example was they were able to build a very personalized email campaign. If you think about, the notion was it was a resort to some kind, and what they were able to do was they were able to grab data from multiple sources, put it into this data cloud, and it wasn’t just personalized in the sense of what… It wasn’t just their past reservations. It was what events had they done, what restaurants had they dined at, what types of reviews had they left on various websites and what their comments were. And then it was able to say, “Well, you know what? They really didn’t like snorkeling, so let’s leave that out and let’s talk about the casino for this person.” And it was really cool. It was a hyper personalized email campaign and it didn’t take very long to set up and it could scale to potentially thousands of users. If you tried to do that with a marketing department that didn’t have this tool set, it’s not possible, probably.
Robert Kramer: It’s manual, yeah.
Jason Andersen: And if it is manual, it takes a year. So it’s not feasible if it isn’t impossible. This was a very cool way to lay it out. And like I said, I just think that they said, by the way, if here’s the industry metric that says the more personalized the email is, the higher your capture rate is, the higher your yield, whatever those rates are, it was substantial. So it was pretty cool. And like I said, it’s always good to see hands-on work.
Robert Kramer: Well, I like that. Mel, what do you think? You have a lot of experience with CRM’s. Do you think that this is an added value for marketing departments? Do you think that CRM’s are already developed enough or this complicates it, or if the data’s right, then it’s a perfect storm?
Melody Brue: No, I think it’s great. I do think, like Jason said, the starting point is great because it is a low risk, high reward situation, and a place to start where typically I would say that the people who are working in a CRM have enough technical ability to maneuver through some of the rocky points as opposed to maybe you’ve throw it into a different department where they’re not really used to dealing with any advanced tools. You may have a little bit more of a learning curve. So I like it for that reason as well. But we are really getting over time here. So Robert, when you started talking, I thought you were going to wrap this up, so.
Robert Kramer: You wrap up. That’s okay.
Melody Brue: Okay. Well, thank you so much for joining us again. Jason, I think we need to do this more often. Great to see your first piece published in Forbes. Great to hear your thoughts on all of the earnings, and thanks for joining us. And for everybody who’s watching, thank you for joining us. Also, Jason does a separate little, I don’t know if it’s a podcast or it’s a one-man show?
Jason Andersen: We’re developing a new podcast. I’ve been making some videos when I travel, but there’s a new one that should be coming out, hopefully… August is the target. So beyond dev tools and more infrastructure, it’s going to be a new… I’ll be doing it with Matt Kimball actually.
Melody Brue: Awesome. Okay. Well, follow Jason on Twitter for that. We’ll have all of our Twitter and LinkedIn handles linked in the show notes. And thanks for joining us, and we will see you next.
