Microsoft’s Industries Approach – Enterprising Insights – EP39

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'd like to talk about Microsoft's Industries analyst event, which took place in Burlington, Massachusetts, uh, this past week. This is an event where I got to attend with a number of other industry analysts to really get a sense, uh, in terms of how Microsoft is approaching these solutions. And these solutions are those that are tailored to companies that work in very specific industries.

Things like financial services, healthcare, manufacturing, retail, so on and so forth. So I get to talk with the product managers, I get to talk with the strategy people, but most importantly, I got to hear from customers, which is really ultimately what I am interested in because there's certainly, vendors have their point of view and they're going to usually paint things in a pretty rosy picture. But I wanna understand, what is it that, uh, customers actually deal with in terms of using these solutions?

What sort of challenges do they have? And then how will they overcome? So let's get into it here.

So, Microsoft, uh, has really kinda taken an interesting approach to going out and marketing their solution to different industries. Uh, they're taking sort of a three-pronged, or I guess three pillared approach to things starting with the Microsoft Cloud. Now, they are not unlike, uh, other SaaS vendors in the marketplace where they obviously would love to see organizations, uh, basically ingest all of their corporate data into the Microsoft platform or into their own platform.

Why? Well, obviously there's a couple things going on there. Uh, you know, the more data that is, uh, imported into their cloud, uh, that's revenue in terms of consumption, in terms of looking at, uh, the actual use of cloud storage.

So there's a revenue component there. Now, there's also the other factor, which is, it is much, much easier to ensure that data, you know, is available and is able to be acted upon things like, uh, automation systems and artificial intelligence if it's all held within a single location. Now, that's not to say that they're not trying to play nice with different, uh, APIs and connectors to other sources.

Of course they are. That's really a prerequisite for operating in today's business environment. You could not have that walled garden approach anymore.

It just doesn't work. Most technology stacks at large organizations or multifaceted with a number of different vendors in terms of, uh, you know, where they store data in terms of data lakes, your data warehouses, uh, and then the applications that are actually used to act upon that data. It is not, it is unlikely that you will only have, uh, one, a platform from one vendor and nothing else.

Now, that's one sort of one pillar is though, is their cloud now second pillar or their, what they're talking about is this industry AI capabilities, and really what that is, it's, they are gone out and they work with a lot of different customers in the marketplace, in very specific industries, and they are gaining and have gained, uh, very, very specific domain knowledge in terms of the different workflows and processes that are used within a specific industry. And why is that important? Well, if you think about the way, uh, we, we look at work, uh, work processes in retail are going to be very, very different than they are in manufacturing.

They're gonna be different than they are in financial services. They're gonna be different than in healthcare. And not only that, there are different industry regulations and restrictions in terms of what processes can be undertaken, what steps were required, uh, what sort of data protection regulations or data handling regulations are involved.

All of that kind of stuff really is very specific to each industry. And even more so if you think about it, it's not only just the industry, but even in terms of where you are within that value chain in that industry. All of that requires a lot of very, very specific domain knowledge.

Organizations like Microsoft, which have a long history of working in these different industries over time, uh, they build up that, that sort of expertise, uh, and knowledge in terms of understanding how that works. And they are incorporating in that, all of that into their various, uh, platform offerings that are targeted at these specific industries. And then the third component or third pillar that they were talking about was their industry partner ecosystem.

This is certainly something that's, uh, increasingly important in terms of having other, uh, organizations that handle different, uh, uh, parts of the value chain, making sure that they're able to capture, share, utilize data from outside of, uh, in the internal system, making sure that they're able to incorporate data from other sources, making sure that they're able to interact with applications from outside the, uh, particular company, uh, you know, uh, you know, platform. Uh, and, and of course then there's also the, the vendor community or third party vendor community, uh, in terms of making sure that solutions can be properly customized. Because, you know, one of the things is obviously as we're, as organizations are trying to deploy ai, there are going to be things that are, that work pretty well off the shelf, uh, pretty basic, uh, capabilities like summarizing, uh, meetings, things like that.

There, you might need to do a little bit of tuning or you might need to make sure that, uh, there'd be guardrails applied to make sure that certain terminology in an industry is properly reflected, uh, within, uh, the tool. But, you know, that is not terribly difficult where it becomes more complex if, where you're just trying to automate and utilize AI to streamline or automate, uh, you know, actual workflow processes, because that could be very, very complex. And that is something that honestly, uh, Microsoft is not in the, generally speaking, they have obviously professional services, but they are not necessarily going to be best equipped to go in and work with each individual customer as they build up their customer base, uh, you know, to customize things.

So that's why they believe in having this strong, uh, partner ecosystem with ISVs consultants and the like, to really make sure that their customers are properly served. Now, I wanna talk a little bit about some of the things that I heard there, uh, that are, are, you know, particularly interesting, uh, if you think about, uh, an industry approach to, you know, deploying things like ai. And, and I should preface this by saying that, you know, one of the other major messages from this event, of course, was Microsoft and their use of co-pilot, uh, dynamics C3 65, uh, among other platforms to really kind of improve customer experiences and customer service.

You know, that is something that is being applied across industries, uh, to make sure that it's not only just, uh, for external customers like, uh, you and I as consumers, but also, uh, customers in a B2B and environ, uh, making sure that they're able to smooth those points of interaction. Uh, so they actually had a few case studies that they highlighted in terms of how this AI technology and copilot were able to, uh, you know, be applicable in very specific retail use cases. Things like, um, you know, reducing food waste and promoting healthier choices through the use of various copilots, uh, you know, innovating in healthcare by the use of something called a DAX copilot, which is really designed to allow medical professionals to, instead of being bogged down with the administrative stuff, which is usually, as anyone knows who goes to the doctor, what are the experience they go in, they start telling the doctor, uh, you know, what, what's going on with them?

And the doctor is usually facing a terminal typing in things into the electronic health record. Well, the idea here with Dax copilot is that it will allow them to actually capture all that information automatically and basically organize it into the right fields so the physician can be focused on the patient as opposed to being bogged down with the administrative work. Uh, I think, you know, they, they actually shared a really interesting story, I believe this from Northwestern Medicine, uh, about the impact there.

And really what it was, it wasn't just about improving the doctor's efficiency, it was improving the doctor's quality of life in terms of giving them more time back to do other things so they're not burning out, so they're actually able to get home at a reasonable hour and spend time with their family. I think that is really where we're, we're going to start seeing additional stories coming out in terms of the benefits of ai. It's not gonna be just about looking at hard KPIs, uh, internally within an organization.

It's gonna be looking about how can that really improve, uh, the life of folks who actually work with the technology. So I think that's, um, you know, certainly the, those stories really kind of resonated with me because it, it goes beyond, you know, just saying, okay, we saved X amount of minutes, you know, uh, you know, writing notes instead of writing notes. That's all of course very important.

And, you know, in terms of individual organizations that do need to show ROI in a very hard, you know, sort of, uh, numbers driven way, but if you look at some of these other more human stories when it comes to how AI is positively impacting their work experience, I think that's gonna be increasingly powerful as we move forward, uh, simply because at a certain point, you're, you're gonna hit limits to what you could talk about in terms of efficiency improvements at a certain point that's gonna flatten out or only increase very, very incrementally over time. I think some of these other stories are going to move the needle more in terms of saying, Hey, if I can achieve efficiency, but also have improved the lives of my workers, well, that's going to hopefully aid in retention. Then of course, we're gonna see a decrease in the cost of, you know, watching people walk out the door, having to bring, have to, you know, uh, spend more money to recruit new people, then onboard them and then train them, getting them up to speed, all of that kinda stuff.

I think all of those types of things are gonna become increasingly important. And the reason why it's, uh, relevant to these industries discussion is there are very, very specific tasks within each of the, these industries that can be considered, uh, burdensome and really negatively impact the lives of workers. Uh, you think of things like, um, in, in, uh, uh, you know, manufacturing in terms of going out and, you know, having to correlate different, uh, data points from various specifications that is tedious work, having to go through all of this documentation, you know, pull out, you know, specification here, match it up with certain regulations there.

That's a lot of work. And it is not, generally speaking, that intellectually stimulated, uh, Microsoft is talking about this from a manufacturing standpoint in one of their demos about how their tools are able to go out and do all that, to go out to all of these different sources, pull in the relevant data, and then, you know, make it much more easy for, uh, organizations, uh, to start on, you know, uh, a new project because they don't need to have a human do that. Uh, of course.

And then the, the other benefit is, uh, these engineers are able to, uh, offload that task onto, you know, a machine basically, so they can focus in on tasks that are better suited to what they were trained to do. Now, another thing also that I should mention here is when we're talking about AI is, uh, the issue, uh, around labor displacement and certainly some of these industries you can look at, uh, or I'll give you an example, uh, look at retail. There has been a lot of discussion about how if you use automation ai, you can cut your headcount and reduce your costs.

That is certainly true, and there are some organizations that are trying to do that. Uh, I think that it is disingenuous of, you know, really anyone talking about AI and just saying, no, no, that's not true. It's just gonna upskill workers.

Well, that only works when you have individuals who are willing and able to be upskilled and also having an organization that is willing to invest that initiative. Some companies are not going to do that. They're gonna look at AI and figure a way to reduce head headcount and, you know, whether that's, uh, good, bad, otherwise, uh, that's, that's not really for me to do, to decide, but I will say that that is certainly going to occur, particularly as AI gets better and more reliable.

Now, what I can also say though is that AI will also be used in many organizations, particularly highly technical ones, to deal with the other issue in the market, which is finding and retaining qualified talent and getting them up to speed quickly. If you think about how AI can quickly, you know, call through, you know, hundreds or thousands of pages of documentation, pulling out all the relevant information, summarizing it, and providing that to, let's say a junior engineer, you're able to get them up to speed so much more quickly than in the past where a lot of it was sort of institutional knowledge that was passed down over time. Whenever it was convenient for a more senior engineer to impart their knowledge to a junior person.

Uh, I think that that is going to be a real benefit to organizations where there's a lot of very highly technical information that needs to be quickly transferred, uh, to more junior people to get them up to speed. And, and it can also be in non-technical situations. It could be, you know, uh, uh, retail's another great example of that where, you know, there may be, uh, institutional processes or procedures that, uh, may suffer from the telephone effect of here's what the manual says of the proper procedure to, let's say, complete a return in a retail store.

Well, it may be over time, you know, it just is one person telling another person the way to do it, and it may not be correct by actually having, uh, you know, vetted information being provided to that individual, that new trainee, that new person in a very easy way, um, that can certainly help them get up to speed and also put them into compliance or ensure that they're in compliance with pro, pro, uh, processes and procedures much more quickly. Um, and another one that, that was actually really interesting, another sort of benefit that I, I heard about and I hadn't thought about it, but if you think about the way, uh, resources, human resources are allocated, a lot of times they may be specialists in one area, particularly in technical areas, but if there is demand for, you know, not necessarily their domain knowledge, but their ability to solve problems or think about, um, you know, how to apply a company solution and it isn't in their core area, well, in the past it used to take a long time to get them up to speed. Again, using ai, you'll be able to, organizations will be able to quickly pull together all of this resident knowledge that's in the organization and quickly present it to, uh, a person in a way that's easily digestible.

And of course, as we, you know, think about co-pilots and this generative assistance in natural language, you know, there are certainly tools that are being built into organizations to allow them to ask in natural language, you know, how do I do this? Or, what's the proper procedure for this? Make me much easier to get someone who already has a certain, you know, uh, technical ability or skill, you know, get them up to speed in an air where that is not their specialization.

So I think there's a real benefit there, and it was interesting to hear about that, uh, you know, at this forum, because generally what we hear about ai, a lot of it is just focused on efficiency or, you know, making sure that um, uh, you know, low skilled workers are, uh, that, that they're able to kind of deflect, uh, inquiries or whatever away from these lower skilled workers so they can lay them off and save money. So, uh, really interesting to hear about that. I think the other key kind of takeaway that I, I had from this particular, uh, meeting is thinking about Microsoft and you know, it is obviously, you know, probably the leading SaaS vendor out in the market right now.

And the reason is they have such a wide, you know, footprint across both, you know, enterprises as well as consumers and all of those, you know, sort of I would consider to be, um, you know, SMBs to mid-market companies that may be, you know, that are using various Microsoft platforms, they are able to do something that's really interesting in terms of, you know, looking at the market and really kind of laying or, or really kinda leaning into their copilot technology and, and illustrating these benefits from the very, very consumer focused use cases to much more complex workflows, that sort of thing. And I think that's important because they, uh, they meaning Microsoft as an OR organization are accumulating all of this knowledge, all of this data on how AI is working and also how AI is not working. I think that's gonna be particularly important as we move through time, as we, we move on down the road here and start to see ai, uh, you know, really become not sort of this add-on, which is the way it is generally being treated right now as an add-on and becomes a more integrated part, uh, integrated part of an application.

Now that being said, I am not convinced that Microsoft is going to follow this trend that some other vendors are in terms of moving to a consumption model. I still see them using a seat based, uh, license, uh, for, for many applications. Again, that's simply because they are a software company generally speaking, and, you know, they need to make sure that they appropriately, uh, frame and capture that value that they're delivering back to their customers.

And, uh, so far I think they've been able to do that in, you know, demonstrating, alright, here are these benefits and you know, it's gonna cost you x number of dollars per seat more to do. So. Now do I think the pricing may be, you know, may it it shift or come down, you know, particularly as competitors continue to leverage or continue to kind of highlight their AI uh, solutions, yeah, it's possible.

Uh, will they potentially move to a partial consumption model on things? Yeah, absolutely. I think, uh, depending on the use case, it's very possible that might happen.

Um, but generally speaking, you know, this is not like an Oracle situation where they owed all of this compute and are able to kind of bake in the cost of, uh, AI easily. So in that sense, in, in one way, they're talking about, you know, really kind of just sort of embedding the functionality of AI into their entire platform. But in terms of how they're pricing it, I still think at least in the, in the near term, we're gonna see it be sort of looked as sort of an add-on additional cost figure getting additional value.

So, uh, really interesting, uh, developments there. I know they're gonna be talking more in the future, not just about copilot, uh, but also about what they're doing around agents. Uh, you know, certainly they have agents.

Now the, the way that they have talked about it in the past was looking at it as co-pilots are essentially, uh, the orchestrators or the orchestration layer to help enable AI agents. And I think that's an interesting approach. We'll see how that messaging lands in the market and, and certainly looking forward to hearing, uh, more details from the company over the next several weeks and months about that strategy.

With that, I wanna move to my rent or rave segment. This is where I take one item in the market and I will either champion it or criticize it. So this week I actually have a rave, and this is really sort of an industry-wide, uh, comment on kind of what I'm hearing from vendors.

I've been having a lot of vendor meetings, both in person and through, uh, various, uh, zooms or teams meetings and what have you. And one of the nice things that I'm really hearing is I am hearing less about, um, hey, we've rolled out this new feature and you know, this new capability and I'm hearing more about, uh, the metrics that really tend to matter to end customers, and that's time to value, ease of implementation, uh, you know, the ease of use of the solution. All of these types of things are really interesting because that's what matters to buyers.

You know, features are great, but as I've said time and time again, and I'm not the only one saying it, you may as a vendor have one thing that works better than your competitor right now, but they're gonna eventually cash up. Maybe they'll leapfrog you and, and you'll be going back and forth like this to the point where there's a certain level of functionality where I believe it levels off and it will no longer be a competitive differentiator. And it'll go back to all of those other elements that are important, whether we're talking about generative AI or really any kind of technology.

Um, so I'm really happy to be, you know, to, to come here and tell you that I'm hearing much more of talk around that. Uh, one of the other things that I'm interestingly, uh, have heard about is looking at AI as a way to mitigate risk, particularly around the area of, if you think of these manual processes that used to be done by humans and by using an AI in certain use cases, you can mitigate certain risk in terms of compliance, in terms of, you know, information being entered incorrectly, information being entered, uh, you know, duplicate information, that sort of thing. All of that kind of stuff, uh, is also, I think gonna be an increasing factor in terms of, you know, a an organization looking at the equation or whether or not they should adopt certain tools.

Uh, you better use the ai. And of course then of course the most important thing is looking at how is AI going to impact employee experiences. I think we've all realized that you can't look at this stuff in a vacuum.

You have to look at it in terms of how does this help our, you know, a company's employees do their jobs better and have better satisfaction in life. Uh, because ultimately you need to retain the employees that you have and also continue to make your organization a place to work and not hamstring people, uh, in terms of not giving them the tools that need to do their jobs. So, uh, continuing to look at that, but right, as of right now, uh, I would certainly rave about the messaging and that I'm hearing about around this from vendors.

Alright, well that's all the time I have today. So I want to thank you for joining me here on Enterprising Insights. I'll be back again with another episode next week focusing on the happenings within the enterprise application market.

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