SAP Acquires WalkMe: What This Means for Enablement & AI

Ken Babcock [00:00:53]:
Hey everyone, welcome to a special edition of the Change Enablers podcast. I'm bringing on my co founder Dan here. We got a few things that we want to talk about. And Dan, like any good mediterranean soul, has his olive tree right behind him. Ready for today's episode? Dan and I were just riffing on a few topics and felt like it could be good to get feedback from our audience on what we're thinking about. You know, we could always spar for days and go back and forth, but I'm curious to hear what you have to think about this, what we're going to talk about today. There's a few things that we're going to touch upon. Thinking about workforce shifts in the age of AI, thinking about the role of it in operations, thinking about some current events.

Ken Babcock [00:01:38]:
And so I just wanted to bring Dan on to get his perspective. So welcome, Dan, welcome to the show.

Daniel Giovacchini [00:01:43]:
Yeah, thanks Ken. It's fun when you have a little sidebar conversation and you're like, hey, we should make this into a real recording and throw it out there. Lets do it.

Ken Babcock [00:01:53]:
Cool man. So I know you wanted to talk a little bit about the future of enablement technology and how that intersects with all the advances in AI that were seeing. AI has become this, I dont know, just sort of omnipresent word, help people make sense of that and what it means for the types of enablement technologies that they need to have.

Daniel Giovacchini [00:02:15]:
Yeah, definitely. So I mean, I think part of what were seeing with AI is you are going to see changes in what's possible as far as enablement for teams and large workforces. And if you're an enablement or operations professional, it's really time to start paying attention and sort of starting to understand, okay, where are these technologies headed and how do I maybe set myself up for success and better understanding these things and eventually making a case to roll them out on my team or my company I'm going to throw out there. I think there's really two paths emerging. Enablement. You have one that's information centric, it's search based, it's chat UX based. You can really think I'm an operator on a team and I am now suddenly able to retrieve information and knowledge much faster and with much greater potential than I was able to before. So think chat GBT, obviously a great example.

Daniel Giovacchini [00:03:12]:
Another one that's been out there in the news a bunch and the venture back scene is glean what these technologies are doing is they're saying, hey, we can go synthesize and retrieve information for operators making queries in a way more powerful way than has ever been possible before. So that's one path. And the other side, I think you also have this path of really task assistance and copilots and work augmentation and that you can think of as Microsoft has started to launch some copilots for their products. But really the digital adoption platform category, which I know, Ken, you've talked about on the pod before, is really emerging to the forefront also, and big news about walk me, getting acquired for 1.5 billion last week. But what you're seeing start to be possible on the enablement front is, is okay, this process centric view. So if you're process focused, you think about systems, you think about workflow, you think about all those operators on your team, what's the environment that they're working in, the tools they're using, their motivations, the knowledge they need to complete a task at hand, and you try and provide it for them in the flow of work. And so I think that's a choice that enablement professionals are going to have to make. When they think about architecting, what is our support information enablement system look like for our teams? Are we going to support people in the flow of work or are we going to expect them to be able to query against information and understand the right questions to ask? So that's a little bit of where we're headed and potentially two paths diverging in front of us.

Ken Babcock [00:04:58]:
Yeah. The interesting thing that I see with glean and any of these very like information focused applications of AI is they're kind of leaning on the fact that we're all just a disorganized mess and we all have this information out there, but all of a sudden we can make sense of it and it doesn't matter where we put it and it doesn't matter where we store it. So, you know, that makes sense why glean has had such a rapid uptick within the enterprise, because there's, there's a little bit of like, well, we've got all this stuff, maybe we've got all this stuff, let's just throw glean on top of it and then we'll make sense of it. Do you feel like there's more preparation needed if you are more process focused, if you're focused on that side of task assistance, automation, what's the upfront legwork that you need to be thinking about as opposed to just like throwing the Band aid on and hoping that it works?

Daniel Giovacchini [00:05:49]:
Yeah, it's a great question. I think a lot of people should consider going back to square one, right? And I sort of saying like, okay, yeah, maybe we have a bunch of information, we already have a bunch of documentation in a knowledge base in an LMS. But if you're going to look at what the potential is with AI now to actually surface information in the flow of work, you should really start to have more empathy for the process and workflow that people are going through and think about architecting your information that way and starting to decide when people need information, starting to understand what your most critical processes are and when you start to build that out. If you can process map and you can really understand your functions and what they're doing, then you're suddenly going to be able to say, hey, we can go put information where people need it. We can start to recognize processes that people are going through and suggest different paths that they should head down from there. And so, yeah, you're going to have to make a choice of like, hey, maybe, do we just throw search based on top of this documentation repository that we already have, or are we going to actually go back to square one and start to think about information in the context of the tasks and jobs people are doing. But does that resonate? Does that kind of land as far as you would think about it too?

Ken Babcock [00:07:10]:
Yeah, well, I think for chat, GPT, and any of these sort of broad based scrape the Internet and come up with a response, everyone talks about hallucinations, and that's largely because there's a lot of conflicting information out there. It's not, the AI isn't taking too many leaps or degrees of separation from the information that it has access to. It's largely just acting on conflicting information or misinformation. And so I think your point around going back to square one and thinking about how do we standardize those processes, how do we think through what is the information we ultimately want to feed some of these tools is saying you're in control of your misinformation. Make sure it's not out there, because ultimately these tools are going to treat everything all else equal. So I think that's really good advice. It's easy to blame some of these tools and say, oh, they're hallucinating, but at the end of the day, it's your information that they're relying on. So going back to square one absolutely makes sense.

Daniel Giovacchini [00:08:09]:
And maybe let's talk about what digital adoption platforms and the new role that they can play. SAP acquires Walkme. Walkme supposedly has this distribution engine to 30 million end users where Waccme technology comes up as users are going through core software systems, your CRMs, your erps, and provides, you know, in the moment task assistance. Right. And it's been very logic and code based to date, but they built this sort of distribution engine for, you know, augmenting and assisting users in their day to day jobs. So, you know, we were talking about this a little bit before, but what's your sort of take on SAP and sort of buying adapt and how that might make certain things possible?

Ken Babcock [00:09:00]:
I almost take a step back and think about why someone like SAP would biowalk me. I mean, they've had a long standing partnership for a while. But for the folks that are listening to this and arent as familiar with SAP, SAP has a portfolio of products that they sell into the enterprise. And making sense of why you would buy Walkme is obviously to enable and support that portfolio of products that theyre trying to sell. And so I think theres a clear path for Walkme to leverage. A lot of this AI technology help people. SAP customers probably more specifically figure out how to handle new products when they encounter them. But then theres also this larger trend.

Ken Babcock [00:09:44]:
I think if you buy what SAP believes about Walkme, which is that theres all this valuable data around digital adoption, around process adoption, across our products, the big macro trend is that the workforce is going to become some combination of humans doing work and software doing work. That software doing work is probably some aspects of AI. And that mix shift is happening. I don't think it's something where all of a sudden AI or software is going to take everybody's jobs. Humans are still going to have to be there. And so setting up these tools for success, setting up processes for success, to be automated, is going to be done by a human. And so I think there's just an increasing importance of enablement tools to help define what's going to get done automatically. And so if I'm thinking about the big vision, why SAP would come in and buy walk me for two plus x markup on their public market cap, it's probably because they see a bigger vision for what that data can do and how that can help enable SAP's portfolio of products.

Ken Babcock [00:10:54]:
I think the other thing that ill just share before I wrap up here too, is SAP has a portfolio of products. Great. I think a lot of listeners here, particularly folks in it and operations, probably look at their organization and say, hey, maybe theyre not all under the same umbrella, but we have a portfolio of products, too. We have an ERP, we have a CRM, we have an expense management system. We have all these other, you know, sort of sales enablement tools. So you kind of have to wear the hat of like, I am my own internal SAP. How do I make sure that I'm getting the right data inputs, I'm driving the right digital adoption for a future where, you know, this makes shift of work. Getting done is going to be some combination of people and some combination of software and AI.

Ken Babcock [00:11:42]:
And so I think that's the big overarching thought. I don't have all the answers there, but I think if you're an it and operations, you should see yourself as sort of the new workforce productivity architect and you should be asking those questions of yourself.

Daniel Giovacchini [00:11:56]:
It's an amazing opportunity, right? Like we're, we're at the frontier. This whole landscape is changing. And, you know, everybody always talks about, hey, what is new technology and automation? It's going to replace jobs. It's going to take away, you know, what we used to know how to do, and all of a sudden we're going to be rendered incompetent and useless for the company. But it's not true, right? Because this is the sort of the mindset shift that you should probably start to take where you're saying, okay, there's going to need to be somebody to determine this mix shift of what are humans doing? What is the technology doing? How can we enable the technology to do more? How can we enable the humans to do more? And so to your point, it seems like a great moment in time for it and operations to look at these changes that are coming and recognize the opportunity within their organizations.

Ken Babcock [00:12:48]:
Couldn't agree more. And I think specifically where we've seen this most acutely with tango is on software rollouts. That's where it and operations are sort of taking things by the reins and sort of starting to think about. Okay, hey, we have an opportunity to make this successful. What are the true capabilities of these tools? What do we need our end users to be doing? I know you wanted to share sort of a quick story from a customer about a software rollout. I'd love to let the listeners in on that one.

Daniel Giovacchini [00:13:18]:
Yeah, definitely. So this is actually a recent one that just came up last week and it was super interesting. It's a huge media company. I won't name who they are, but their training department was really tasked with looking at all the software rollouts that are happening across the company and saying, okay, what do we need to do? What do we need to get done to make these a success? And, you know, it's hard for us sometimes to relate, I think. But a lot of training, so much of it happens in person in classrooms, and it happens with PowerPoint slides and it happens with, you know, video recordings of these sessions and, you know, those slides and video recordings and those are the artifacts that, that learners are basically supposed to take and, you know, say, okay, suddenly we understand how to use software. Its a little bit comical when you think about it, but this is sort of the best that a lot of people have out there. And if this is you, you shouldnt feel bad, right? These are the best tools that have existed out there today. So really cool tango story.

Daniel Giovacchini [00:14:21]:
This group sort of discovered tango and they said basically they estimated that across all the training, preparation time, creating the content, planning for these in person classroom sessions, doing the follow ups, it was going to take them 900 hours across their staff. And this is where you look at it, you say, okay, there has to be an opportunity for technology to help here. There has to be a better way. And so what they've done is they had a team of four to five trainers that were sort of tasked with making this content, planning these in person training sessions. And they said, instead of doing all that, we're going to use tango. We're going to go capture the core workflows that people will actually need to go do to get their job done. And we're going to make a library of content that's very process specific to how you do your job. And then what we're going to do is we're actually going to introduce people to software by using the software and then having these guides live and breathe right in the software right where people need them.

Daniel Giovacchini [00:15:30]:
So their learning experience then actually it wasn't, you know, showing up to the office on that Wednesday that you didn't really want to go in and sitting in a classroom and listening to, you know, two to 3 hours of, okay, first we're going to walk through the basics of configuration and now we're going to, you know, go through what it's actually like to, in this case, you know, a big part of it was CRM. So here's how you are now going to create new contacts and company records and deal opportunities and have these back to back sessions and then go back home and expect to like, okay, the next day, just log in and remember all that. Instead of that, the experience is now, okay. You don't need to come into the office. You're going to go use the software for the first time and you're actually going to do the processes to learn them. Right. So you're going to go in and you're going to get handheld assistance through your software as you start to use it for the first time. And so again, they looked at it and more, more exciting stats to come, but 900 hours of preparation time that they estimated they probably cut down to less than 100.

Daniel Giovacchini [00:16:40]:
And they're so much more excited about the user experience and the potential and no need for travel. And they don't have to actually tear up their work week to, to do software training. So pretty excited about that one. And to your point, what's your SAP? How can you start to think about enabling the new ways of what's possible for getting productive and doing your job?

Ken Babcock [00:17:03]:
Yeah, I mean, that's super compelling, right? You save somebody 800 hours in preparation, that probably doesn't even account for all the end users on the other side who are like, oh my gosh, I have to go back to the video. I have to go back to the training because I didn't get it the first time. So, you know, let me, let me bash my head up against the wall and figure this one out. Obviously, that's a really compelling ROi. And I also think, too, you know, there's probably a time and a place for kind of in person learning and training, particularly when it comes to soft skills. But when it comes to software, you know, and real tactical process, that information just isn't going to be retained. So I think, I think that's a really powerful customer proof point. And with that, this is a little shorter episode, a little vignette with Dan.

Ken Babcock [00:17:49]:
We're going to make these maybe more recurring if people like them. So give us your feedback. We'd love to hear your thoughts. And thanks again, Dan, for joining the pod.

Daniel Giovacchini [00:17:57]:
No, this was a blast. Let's definitely do it again.

Intro/Outro [00:18:03]:
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