Strategy Inc (MSTR) Earnings Call Transcript & Summary

All right. So we have people joining. Hello, everyone. We're going to get started here in a few seconds. I'm just going to let everyone join in. All right. So hello, good morning, and welcome to our webinar on the future of BI. I'm really excited for this one. We have 2 amazing speakers with us, both of you have impressive backgrounds in the BI space. If you don't know me, I'm Holly Stevens, so I started out in product management and now moved over to product marketing team. Now focused on go-to-market and strategy. But today, I get to ask hard hitting questions. So who are we speaking with, Jose and Rowan, I'm going to turn it over to you all for brief introductions.

Rowan, you're a guest speaker, I think you can start.

Great. Great. Well, thanks, everyone, for joining. It's so wonderful to see so many folks, and it's great to be here with you both, Jose and Holly. So I'm Rowan Curran. I'm an analyst at Forrester. My main coverage areas are data science, machine learning and artificial intelligence, but I am definitely very deep into the BI world. I come from both a practitioner and a researcher -- practitioner and a research perspective. So I 5-1/2 years being a data developer and managing a business intelligence team. And before that, I was at Forrester as well looking at the business intelligence and advanced analytics space. So I'm really excited to talk about our topic today. I think it's really, really exciting.

Thank you, Rowan. Hey, everyone. Thanks for joining today. My name is Jose Nocedal, and I lead the product management team here at MicroStrategy. So I'm pretty excited to be discussing today with Rowan and Holly what is the future of BI.

Yes. Amazing. So again, we have Jose from MicroStrategy, and then you have Rowan from Forrester, you're going to be getting these amazing 2 perspectives as we go through the webinar, we're going to be talking about trends that we see being really relevant to you all as you move forward in the BI space. And we'll take a lot of questions at the end, I promise, so make sure to add them in the chat as we go through the presentation. And a note that is, I'm sure we'll go through a few road map from the MicroStrategy end. So know that everything is under safe harbor. So anything that Jose mentions in terms of future features, time lines may change. I know you love to hear it, but just keep that in mind. And in terms of future trends and the ones we'll be covering today, I'll turn it over to Rowan to take us through those so that you kind of get that framework before we go into the deep dive. So Rowan, I'll give it over to you.

Great. Great. Thank you so much, Holly. So I will just share my screen really quick, and we'll get right into it. So today, as you can see, we'll be talking about the future of BI. And specifically within that, we're going to be talking about the aspects of augmented actionable and pervasive BI and how that's going to help us improve our decisions and our organizational outcomes moving forward. So just to bring us all together here, enterprises today, we rise or fall on the amount of data that we have and the efficacy -- the decisions that we make based upon that data. And these are decisions made by leaders, like most of the people on this call probably as well as by all of our employees, who are also all employees on this call. And we are all together enamored by data and its potential. But one of the issues that a lot of us are facing today is that we can't connect this data to outcomes, insights and actions that really will improve the bottom line, and ultimately all of our business goals for our organization. And the way we see this transformation happening at Forrester to move from what we call data aware, which is where a lot of businesses have been moving into for the past 10 years or so and really that the first stage of becoming what we call an insights-driven business. So to move from being data aware to insights driven, you have to move through the stage of being data-driven, which involves a lot of different components, organizational process, things to do with technology as well as strategy. You can see some of them laid out here. So it's setting goal, building metrics, discovering these insights, validating and experimenting with these insights. And then implementing within your applications, making decisions on how to act with them and then linking those decisions to actual business outcomes and then learning continuously throughout the life cycle. So this sounds like a tall order. But what we have seen is that organizations that actually are able to build out and execute on this type of architecture are really seeing a lot of advantage in the marketplace. So, compared to beginner firms, firms that are just data aware to these advanced insights during firms that I was just talking about, the advanced insights-driven firms are more than 2.5x more likely to have double-digit growth and more than 8x more likely to have more than 20% year-over-year growth. So there's really a large gap between just being data aware and really being an insight-driven business, which is what we're going to use a lot of the advanced capabilities in future looking BI systems to do. There's also the importance of being future fit here. So looking into these future BI trends as well as broader future technology trends is going to help you become a future-fit organization, which, as you can see here in our data, that actually bears out in terms of whether organizations are growth leaders or growth laggards. So folks who, according to our scale are in the leading edge of future-fit organization, which is a little matrix that we use, they're 2.5x beyond the average industry growth and folks that are not pushing for future fitness are actually below the average industry growth. So what is driving this? So we've seen from anecdotal evidence that less than 20% of enterprise data is actually being used for insights. And then on top of that, less than 20% of enterprise users are actually interacting directly with tools that give them insight. It's not that 80% of people that our enterprises are not using data. They're our managers or our partners that were giving PowerPoints or printed out PDFs or even just digital PDFs with data on them, but they're not going to the source of the data, interacting with it in a place that they can actually make immediate tangential -- tangible decisions on better outcomes for their business. So how do we move from becoming data aware to insights driven? So there's a lot of different pieces to this. And in the BI world, we see it as becoming more impactful with insights-driven actions that are based on augmented capabilities, unifying these decisions, personalizing them for all personas so that they're adaptive, future fit and then they pervade across the entire business. So that's a big mouthful right there, a lot of stuff in there. But there's five kind of key components of this. There's -- as you can see at the top there, the actionable component getting these insights into our actual business flow so that they can change customer experiences, supply chain partnerships and other things like that, making it unified and personalized. So this is the bottom and the top, really looking at the data underlying everything to the actual personalization of the insights reaching folks, to augmenting the data, making it adaptive, pervasive -- adaptive, pervasive and impactful. So five is a lot to cover in one webinar. So we're actually going to narrow this down to 3 really key aspects of the future of BI. The actionable component, the augmented component and the adaptive pervasive component. But before we do, I just want to very quickly tag into the unified, personalized and impactful piece because we don't want to leave these completely behind. We just can't dive into them too much today. So becoming more unified and personalized, this actually goes across all the other aspects. So this is really about making sure as we're building out our BI system that we have a unified data model at the core so that we can actually derive insights that are the same across the various enterprise groups and organizations, and then actually delivering personalized insights so that the insights are delivered in a format that is consumable and is palatable to whatever type of user you have. So some users might like to have visualization, some might like to have plain English sentences. Some might like to have just a bunch of numbers on the spreadsheet. So there's different ways that people like to consume things. And then the other piece of this is making -- it's looking at the impactful decisions of BI. So really starting to integrate metadata. So again, bouncing off that unified piece as well as looking into leveraging digital workers, so robotic process automation to implement some of these advanced BI decisions. And then really moving to more automation of some of these very simple operational decisions that can be informed by BI and then executed digitally by digital workers. But -- so that's a quick dive on those 2, but now let's get really deep on actionable, augmented and adaptive and pervasive BI. So, we'll start off with looking at actionable BI. And what we're talking about here is really infusing actions into BI apps. So today, most BI applications allow you to derive insights, get some kind of information, maybe even develop a better sense of knowledge about the topic. But it's much rare that we actually have a single click button or a single action within a BI application to drive up to the actual changeable business outcomes that we want to expect with this information. So this is all about integrating the actual action endpoints into the apps themselves. And then, we want to -- going kind of off that, we want to embed these workflows deeply into analytical applications. So there's a lot of business applications that have a lot of information within them and require a lot of knowledge to actually execute them. But if we start to embed more BI and business knowledge directly in these applications, as a lot of the big business application vendors have started to do, then we can actually add knowledge directly at the point of decision for all of our users, which is really going to allow us to directly change whatever use case we have going on. And so then that can actually be used to upgrade these business applications with embedded analytics. So doing things like delivering a dashboard directly within the context of some of the most used business applications today, like, say, e-mail or a web browser. So it's really about connecting the insights to the actual business applications that folks are working in every day, because one of the things that we all share in this broad landscape of BI applications. I remember my organization used, I think we had 4 or 5 different tools, and we were on the low end of tooling landscapes for business intelligence. So going beyond those components, one way that we can really start to integrate actionable BI is looking at things like translytical databases, where we can bring together both the transactional applications and the analytical applications in one platform with one sort of paradigm around it, so that we can execute all different types of enterprise actions directly from the same paradigm. And then here, this might be one of my favorite ones. The future of BI becoming more effective is really going to rely a lot on augmented capabilities. And when I say this, this is really around infusing some of the more advanced analytics capabilities, especially around machine learning and what is often called auto ML directionally into business intelligence applications. And so what you can do here is actually use these auto machine learning or auto ML applications to create ambient BI. So basically, these are components of BI platforms that will essentially auto train a model on your data based upon the shape of the data to give you insights into it, even if you don't have really strong data or statistical background around that. And what this ultimately adds up to is BI being added to artificial intelligence, with the broader systems around machine learning and that equaling out to augmented BI. And one of the really cool opportunities about this is that it's not just that it enables business intelligence to add more complexity and deeper insights into their actual applications, but it also enables data scientists to have better workflows themselves because it allows them to get better insights out of their initial data sets, to explore the data more easily and ultimately to build a better model, which then will feed back into the business intelligence organization. And so reaping the benefits of integrating machine learning and business intelligence requires some new efforts that haven't traditionally been part of business intelligence. And one of these is model operations. So to just very quickly to go through this, this is really just the idea of having a deployment organization and a continuous integration, continuous deployment organization around models for machine learning in addition to your standard application release, your standard data release, which can enable you to increase the transparency and explainability around models. You can see as they're drifting from their accuracy and their initial data, you can see kind of why they're drifting, what data sources are driving behind that. And then you can use the model to kind of retrain and increase the accuracy as well as focusing compute resources around that. So that's for kind of the extended augmented BI space, but it's really important for building these future fit BI organizations that have much more intelligence than we've traditionally been used to. And then some more pieces of this are around natural language querying and natural language generation. So a lot of these augmented BI capabilities might not be doing cool forecasting models or some kind of customer churn. It's just in the simple ability to type in a plain English sentence and actually get data results on the other side, or in doing some kind of data query and having a natural either English or whatever language sentence generated on the other side that is readable to a human. So instead of just having a table that says we have 5 widgets that were produced in factory 1, 2, 3 and 4, you might have a sentence that says, we had 4 different factories that produce 5 different widgets in the past week period, that is a single sentence. So these natural language querying and natural language generation capabilities can be challenging to implement if you're doing it on your own, but many different BI platforms actually integrate them directionally today, which is a really cool feature for the future. And then finally, we have this piece around insight being pervasive and embedded in all systems of work. And really, this build off of a lot of the stuff that I have been speaking about previously, and this is really where the rubber hits the road and we actually scale up our organizational intelligence and get into this brave new world of being augmented humans with better intelligence because of all the machines around us. So this is around having us embed intelligence for business applications, enterprise collaboration platform and enterprise productivity platform. So, one of the big things about the future of BI is that we're really seeing business intelligence become a much broader umbrella. You might have started to see that your own organization over the past half decade or so where enterprise and cognitive search, business intelligence, data science, analytics, they're all kind of converging into a single flow of enterprise knowledge and enterprise intelligence to help us do our jobs better, help business processes move smoother and it helps to relieve a lot of the pain points that we have with our customers and with our internal organizations. And one of the really cool places that we can put a lot of these embedded intelligence into our browsers, which as I mentioned before, is probably the most common workplace productivity tool. And being able to embed business intelligence capabilities directly into browsers, either in the form of cards or pop-ups, that really allows us to add this embedded ambient augmented intelligence directly into our work streams that will allow us to make the fundamental changes to really enhance our productivity and capabilities. So what this means is that modern BI analytics is much more complicated than just a simple authoring and consuming of reports and dashboards. We have a list of a bunch of different components here. And they are all just -- it can be overwhelming in terms of how you build these things out. So in order to have a future-fit BI organization, you really want to marry business intelligence and application development. So you have complementary top-down and bottom-up approach. So in order to do that, you can either have a top-down approach where you have clear support for business requirements, it's still siloed. Or you can go for a more bottom-up approach, which is not agile, but you have clear business requirements at the beginning. But what we can do now in this new future fit BI organization is really have kind of dual stream so that we combine our top-down and bottom-up approach. So we can have -- basically, you can have multiple tactical projects that are going from a top-down approach where you have an executive says, "I want to know this particular outcome or aspects of our data sets here for my KPIs or for my performance review, can you deliver that to me " And then you can also, at the same time, have a bottom-up approach that is cleaning your data, developing better insights and informing those tactical projects that is happening at the same time and is actually building a longer-term success story. And then ultimately, that will lead to a set of continuous improvement projects that build better data structures and a better data organization and make you a better insights-driven business. So as I talked about before, the technology behind us are extensive, on the front end, you have portal and search expanding the BI space. On the back end, you have things like data catalogs, machine learning, feature catalog, ML Ops piece, semantic layers and knowledge graphs that are coming in a big way now. And then to actually deliver this, we have insights-driven businesses that are operating differently to deliver pervasive insights, harnessing actionable insights from these analytics and building cross-functional agile teams to actually do this continuous delivery of insights and continuous building of insights over time. So just to bring it back to where we started. We have this -- at the center, we have here the insights-driven business architecture, so setting goals, building metrics to enable ourselves to learn and improve continuously. And then supporting that we have all of these different aspects of future-fit BI, which will enable the insights-driven business along with a lot of other different technologies that we can't cover today, but really business intelligence is one of the key enablers of an insight-driven business for the future. And there's just so many cool tools and capabilities within the BI space now to enable this, even though we have a lot of challenges to overcome from our legacy systems. So I will wrap it up for myself there. I think I've chatted long enough, and I will pass it back over to Holly. Thank you all so much.

No, that was great. Thank you so much. All right. So that was essentially -- you got the trends. You now know kind of this high-level context of what we want to jump into. So when we're thinking, let's just jump right into that first trend, enterprise BI will affect tangible business outcomes with actionable BI. So focusing in on the actionable BI bit, Jose, when you think about that in terms of the MicroStrategy platform, what comes to mind? Do we have a specific product? Do you have something we're working on? How does that tie back to MicroStrategy?

So I know that we're talking here about the future of BI, but I see one thing that we can show about the press and it's HyperIntelligence. Like to your question, I think HyperIntelligence covers not only one aspect of what we've been discussing but multiple, right? HyperIntelligence is completely pervasive. You can embed analytics in multiple of the enterprise applications that you use on a daily basis. And it is a pretty powerful solution to deploy, right. Using Hyperintelligence, you can augment the experiences of all your users just by deploying, as Rowan was saying, something on your browser, right? So I can show an example real quick if we have the time, I'll try to be with super brief here. So maybe I can share the screen.

Yes. So Rowan, it looks like we're still seeing your document. So if you unshare.

I'm sorry. I will stop sharing. I apologize.

No, this works.

So this is just to prove [indiscernible]. So this is not reporting. So -- but let me show you some quick example of this, right? So for whoever has not seen HyperIntelligence in the past. So one of the products that we have in the HyperIntelligence line is the abilities of browser extension, right? And this is completely related to what Rowan was saying. So with HyperIntelligence what I have on the screen is just a CRM system, right? This is something that your users interact with every day. And without any major thing, without actually having those users trying to go and find the answer for their business, what HyperIntelligence allows you to do is to get that information right to you. And that will help you, your business users to make decisions in a faster way, and pretty informed decision. So this is something that, again, I know we're talking about the future, but this is something that is checking some of the boxes that we are seeing as the analytics and business intelligence trends for the present and for the future.

Yes. I think that's great. And then -- so for organizations that want to use HyperIntelligence, do they have to use the browser extension? Can they use SDK? How does that work for them?

So another thing that Rowan discussed today is that people or users on a late age, we're also looking for flexibility, right? And when we're looking for flexibility, you need to provide the right tools to be to customize to tailor the experience. And to your specific question, Holly, yes, so HyperIntelligence, you can also deploy it in 2 different flavors of the SDK. One, if you want to augment any enterprise application that your users are interacting with every single day, you can customize, you can white label the extension, right? So here, for example, you can see that instead of the traditional HyperIntelligence, I can add my own icon, I can modify the default status for the cards that my users are interacting with. I can also modify what website will these parts be displayed. And in addition to the ability of what we do in the extension, what we can also do is just with a simple code snippet, you can inject that into your own enterprise application and then you can also start using HyperIntelligence there. So in shareholding, 2 flavors, they are built to white label the hyper extension and the hyper-SDK if you want to have that functionality without the need of installing a browser extension.

Yes. And I think that embedding part like you're saying, right? So if you use the SDK, that's really important if your organization might have security concerns around that browser extension, et cetera, always good to have that option. All right. So moving on to trend #2. So if you were watching and following what Rowan was talking about earlier, the second trend is that enterprise BI will become even more affected with augmented capabilities. And so -- this is a favorite one for a lot of us. When I think about analytics, when I think about the data landscape, I feel like augmented is something that there's a lot of buzz around. So high level, can you both kind of speak to your opinion about why augmented -- it's going to be a foundational piece of BI moving forward. So Jose, I guess, you can start and then we'll move over to Rowan just about that opinion on that.

Sure. We definitely see an important trend on augmented, right? This is something that we think is possible with Rowan in the past, and with some of our customers. Now one of the things that we are doing on this front was, our vision was already shared during [indiscernible]. So whoever has not had the chance to watch our CTO, Tim Lang doing MicroStrategy World. I recommend you to watch it as it is available in our website. But one of the things that we said during that session is that we want to augment the experiences, but we definitely want to add value to the workflows that users [indiscernible] drive with every day. And yes, we want to bring technology such as machine learning and artificial intelligence, natural language to those MicroStrategy workflows. Now, one of the things that we have been working on, we're exploring some idea is how do we start us providing more insights into the -- from the MicroStrategy application. So what I have on the screen is just a quick example that we also shared during the World. And again, it's just an area that we're exploring and how you can start monitoring data that is important to you, right? And the idea here is that without you having to actually set manual alert or manual notification, we can let you know when the data is changing, right? And that is also related to the model of that Rowan before. We are running machine learning models in the background to see how the data is fluctuating and whether something requires your attention or not, right? The other thing is that, of course, we want to make the data easier to understand and we want to provide suggestions on how to take action on those -- those changes. So what you can see on the screen is that we're also providing natural language capabilities to explain to you why the data has changed? What something might require your attention? And what are the main drivers that are causing that change, right? So here we're taking some of the trends that Rowan was explained at the beginning of the session, we were talking artificial intelligence, machine learning and natural language right, and at the end of the day, bring more insights to the users so that they can take actions based on their data.

And just to kind of pull us back a little bit to look at it from a higher level of view, I thought that was really great. One of the things that I think we should think about when we're thinking about augmented BI, it's not just coming at -- augmentation is not just coming from one direction, right? They're coming to business intelligence from a lot of different directions. So we're seeing, for example, in addition to the auto ML and the embedded predictive capabilities, you're seeing the natural language querying and natural language generation being more and more of a basic part of the business intelligence platform. So one of the actual issues that we see with augmented BI is that a lot of the time, users will not take advantage of these great, more higher intelligence capabilities within the platform. But if you have things like natural language querying and natural language generation, that kind of -- to go back to our embedded actionable trend that basically just embeds the insights directly into your workload in a more naturalistic way. And some other pieces of this that we're seeing is improved knowledge management for data and insights using augmented BI, the integration of knowledge graphs and other ways of managing metadata and the understanding of the data itself as well as providing more explainability at the insights. We're seeing a lot more kind of BI platforms integrate automated descriptive statistics for data sets so that business intelligence users or even like I was talking about before, data scientists can get quicker insights into their data without having to do any manual work on their side. So I really -- the augmented BI is near and dear to my heart because data science and machine learning is my main focus and favorite thing, but I think particularly within BI, it can really move us from this plateau of 20% of people getting 20% of the insight, up into -- we'll never reach 100% because people are people, and to a much higher degree of enterprise users using insights within their daily work tasks.

Yes. I love it. And then when we're thinking about Jose, the watcher feature. Is that something that would then be sending out alerts across devices? Or how do you guys imagine that happening and improving that efficiency for users?

I mean we want to send alerts to multiple firms, right? And one of the things definitely that we're exploring is the traditional email, right? At the end of the day, you're also on your phone. Like now that we are finally getting like moving on from the pandemic like people are going back to mobile, right? So you want to send notification to your mobile device, your basic application. And again, one of the really cool things about this one is that those alerts are -- you are not going to have to set them up manually, right? We want to alert you when we think when the system detects -- when the platform detects based on its logic, that's something requires your attention, right? If we see that something is trending down or up or it's like crossing some value that we have noticed that is the regular value, we want to notify the right way. So what we're doing there is we're simplifying the experience of you having to manual send notifications. And sometimes you might just get noise, so many times you might not want to get those, right? So it's important that we apply the right model to notify you when it makes sense and what something requires that you take a look.

That's awesome. I like the combination of being able to watch the data as well as actively alert our users, I think it's really powerful. All right. So now moving on just for the sake of time, I know we're approaching lunch time, everyone. So that third and final trend, so enterprise BI will be pervasive and embedded in all systems of work, right? So this also ties into a particular statement from the same Forrester report that states that only 20% of enterprise decision-makers use BI applications hands on, right? So that means that a lot of people in an organization wait to get data from others to embed in Excel or PowerPoint, I know that we actually just had a question about PowerPoint in the chat, but only a limited number of users are actually in the data applications. And Rowan kind of actually mentioned that a little bit earlier as well, how do you both think that embedded analytics can increase that 20%? Is that the answer, the key to a lot of that lack of adoption. And I guess we can have Rowan go first on this one, but a really interesting topic.

Yes. This, I think it's one of the most interesting topics in BI and honestly, I'm really surprised that we haven't had deeper conversations about it in years past. We spent so much time focusing at our companies on meeting our customers where they are, right? Like we want the interaction with our company and with our enterprise to be as seamless and smooth as possible. But we haven't really thought as much about, okay, how are the interactions within our company and for our employees. And can we go and meet our employees where they are with the data. So the ability to embed BI directly within all of our systems of work today, I think it's a really huge and critical trends to not just improving business processes and workflows, but actually moving us to an enterprise culture like not just within one enterprise, but for all of us as knowledge workers to a certain degree, but to moving to a place where insights and the data behind it is not just like a daily part of our work, but it's integrated into every step of everything that we do. And ways that we're seeing that today are integration with the business collaboration platforms like Slack and Teams and all these different chat platforms as well as integrations with standard like Office applications, Microsoft Office, Google for Work, all these different things. And it's really just an amazing way to get insights directly to the people who need them where they are without having to drive them to a business intelligence application. And I'm sure many of the folks on this call, myself included, have had experience with trying to get business users to go and use BI applications and it is incredibly frustrating because they don't want to leave the applications that they're using already. They just want to stay where they are. So I think this embedding of insights is a really, really important part of having a Future 50 organization. One way you can think about it is you have an experience this directly, either within products or within demos, as a lot of the business intelligence platform a few years ago started to integrate drill-downs when you scrolled over a certain metric or something like that, and it just popped up the data behind it. That's kind of how you can start to think about some of these embedded insights, that you'll be within some kind of enterprise application, you'll scroll over a name or you'll click into coworkers project, and it will pull up a bunch of data about it for you. It allows you to continue to go about your day and make decisions without having to switch to a different BI application, find a report, yada yada yada. So Clearly, I'm very excited about this particular trend because this causes so many issues with enterprise insights of just not getting the data to the people where they're actually doing their work.

Yes. I think that's a great perspective. And then when I think about MicroStrategy, right Jose and what we've been doing, I think we have a lot that addresses, obviously, embedding and I'll let you speak to that. But also one of the latest flashes in case anyone on this call hasn't seen it, is this new concept of custom applications, right? So even building an entire application. So from embedding, it might be a simple visualization into an existing portal versus building that app. Jose you kind of speak to how we're addressing the third trend?

So on the applications topic holding, yes, you talk about it at the beginning, right. And it's something that we released last Q4, right, last December. And the idea behind it is to be able to provide the full flexibility of the MicroStrategy platform with a pretty low learning curve and then be able to take that personalized experience and embed it anywhere, right? So just to show you a quick example of what we mean by this, right? And also like the ability of not having to recreate multiple applications and maintain multiple applications just because there are some differences on the experience that you want to provide, right? So if I show you some quick example of what we've been working on, right? So let me show you what we have here on the screen. So what we did is that this is something that the application concept was released back in Q4. But one of the things that we have recently added, and something that we are making a lot of progress on is provide our ability to have more flexibility on what you can do. So in this case, what I can do just to show a quick example is, say that you just want to have -- you want to white label the experience, right? You want to change the icon that appears to default on library. Well, you can do that and then you can just keep making changes to the editor, refresh the browser. And keep in mind that this is completely applicable to the embedded scenario because you can just take this when you are embedded, and then you're going to have the same experience whenever you have embedded this MicroStrategy application. The other thing that I wanted to show you super quick today is the ability of having like different experiences depending also on the group of users that are interacting with the product. So what I have here is that I have what I call a red app, a blue app and then just kind of MicroStrategy library experience. And you can notice that the changes here are that if I go to the to the standard vanilla version of MicroStrategy, I will see that these colors are in blue, they are green, like basically this is what I design my dossier to look like. But the difference, though, are that just reusing the same dossier, what I can do is that I can say another color palette like here. And then I can have that being the default experience that my customers will use when they get to this application. So in this one, for example, you can see that the same dossier is looking with a red color palette, the blue one is just in the blue ones. And keep in mind that I have also customized, for example, collapse by default the toolbar, right? So you imagine that you can take these as embedded on your portal and the branding, the color scheme is going to be consistent with the rest of your enterprise portal or applications.

Yes. I think that's really a great thing, right, because it's not only showing embedding, right, but it's also showing how we can be creative and more personalized for different user groups. And I think applications is really exciting for MicroStrategy. All right. So I'm going to kind of end before we start taking these questions that are coming in. We went through 3 trends, obviously. But out of the 3, which would you label as the most important one to focus on. So the people that are listening what do you think should be a top priority if they had to choose one to focus on right now, what would you guys say? I don't know who wants to go first because it's -- or is it a trick question? It could be a trick question.

[indiscernible] personally, and I think that's a completely trick question. I think it's hard to pick one. I mean even today for example, we had to figure 3 trends, right? And I think all of them are related. So I think you're trying to trick us here. I think that at least for me, it's not easy to pick one. I think all of them represent part of the future of business intelligence.

Yes. And I definitely would agree that they're all very important. I think it's -- what is the most important to a company depends on where the company is today, I think, and what the immediate goals are. So like if you have a data science organization, for example, that is pretty robust and want to start integrating with your business intelligence organization and you have a good BI technology, you can start to build some of these augmented insights already. But if you're not quite ready for that, but you have a good data model behind it, you could start to look at the embedded and pervasive analytics because that would just be delivering insights you already have. And the actionable piece, if you already have robotic process automation or you really have very strict business processes that don't change very much, that might be a place to start. So I agree, they're all very important and critical and where you start really just depends on where you are as a company and what your short- and long-term goals are around business intelligence.

Yes. I think you're completely right. I think we have also people agreeing that does depend on where that company is. All right. So let's move on to answering some of the questions that are coming in. And everyone listening, please make sure if you have any questions about what you saw, anything we didn't cover. If you have any random question about features that we might be working on, go ahead and put them in the chat. But let's start with number one. The first question that we saw, and I know that we were trying to answer it, but just to get a good answer here in terms of if we're actually working on it or what exists. Is there a MicroStrategy dossier extension for Microsoft PowerPoint. So I guess that would be a Jose question.

It is not at the moment. If you are an existing customer, please do help us to allows this request. It is something that we have explored. We have some ideas on that front. But at the moment, we don't have a product that can do that.

Okay. Good to know. Second, is there -- are there any future enhancements in the pipeline for alerts and visual insight or dossiers now. One of the things our clients need is the capability to create projects. For example, if they identify an issue in a given KPI or metric, for a specific attribute combination, they want to take it on as an improvement initiative and track it moving forward. So I guess Jose again, any future enhancements there.

Yes. I think this is part of what we were showing with the watcher functionality, right? The idea here is that you don't have to manually set the alerts, like we're just going to be alerting when we -- when the platform detects that something requires your attention. So yes, we're bringing those capabilities to dossier. I think the example that I showed today was with a KPI visualization, but definitely that is the first step on this vision.

Awesome. And then another interesting question we got was from Michael, and he said, fundamentally these insights or the insights that we were referring to here in the presentation, need to be embedded into the business process. How do you see that becoming more pervasive? And is this something where you think Hyper is playing more and more of a role. So I think you guys could probably both speak to how insights can be embedded in a business process. And Jose, I would expect maybe we can talk more about how hyper could address that.

Yes. So I'll jump into this real quick. So I think we already talked about a lot of this, right? So there's -- if you have something like a browser extension, it's very easily to embed insights directly within any web-based application because it can pick up text or other things from within that application and then give you insight based on that. So that's actually one of the nice things about that type of embedding of insights, and it's not actually -- it doesn't have to be tightly coupled to the application itself. It can just be kind of reading content and then associating relevant data in your database behind it. And then there's also the other side of that, which is embedding the insights directly within specific business process applications themselves. So that either requires native capabilities from that vendor themselves or some kind of integration point with outside BI tools. And one of the, I think advantages that I mentioned before, to the embedding of these insights is that can really start to change the mindset of organizations at the individual team and the department level around their behavior because they have access to data like directly within their workflow. So, I think looking at the browser-based piece, the division-piece as well as the productivity tool piece because of the emerging integrations with Slack, Office, all those type of things. We don't spend so much of a day in those type of applications. So having more knowledge and insight there would really help us make more use out of that time.

Yes.

On the Hyper front, yes, it's definitely something where we see that Hyper is completely pervasive. It helps you to augment the experience on all of your enterprise applications. And yes, we see that we can include more insight capabilities.

Yes. And I think that, Michael, your question too, just as I was reading it, Hyper, you can really think about that workflow A to Z. Where is the user going to see it first, right? Like Jose showed, what's the action you want to embed within that card header. There's a lot you can do with it. And I don't know if we specifically talked about the actions you can add, Jose, but you can link out to a page, you can add an e-mail or a specific sales force page. So a lot of things you can do with Hyper.

Yes. You can add like any action, you can have the bottoms on the card. And then from there, you can start taking action. And that's what we were showing HyperIntelligence as an example of the actionable trend on analytics. Because right from the card itself, you can trigger actions on other systems or back to the MicroStrategy platform.

Yes. All right. Awesome. Next question, we did get the question where is watch data available. And I'm assuming you're talking about the watcher feature that Jose did show that is on the road map. So you can't access it yet. But Jose, I mean, we're hoping maybe soon, right, for this? We'll see. I know you can't speak to the time lines, but obviously, on our road map. Next question, can we define our own color palette and push that out to our organization so everyone can use it?

Not yet, but quite a prediction. Stay tuned. Remember that we released -- we release quarterly, and we also released monthly. And keep an eye on the release, it is going to be out [indiscernible].

Yes. And that's a big thing that you just said you didn't know MicroStrategy now does have monthly releases. So try to keep up with this cadence. We have a lot rolling out really fast. So keep that in mind. Next, we have a question about writing back to a database. So will MicroStrategy dossiers ever be able to write back to a database, talking specifically about things like notes an end user would create based on findings.

The answer is yes, but with a caveat, pretty soon as well. So it is something that is highly prioritizing the road map. Again, same as with the previous answer, keep an eye on the releases. The end of Q2 is coming soon. So stay tuned.

Awesome. All right. And wrapping up, if you have any other questions, again, we have 13 minutes, but we have this last one, and it's going to be the last question if we get no more. So question, since the high adoption of mobile, how do you see this concept of mobile apps where the browser is not the starting point? So I guess we're kind of looking at, if you're not in the browser, what can you do with MicroStrategy to build those apps?

There's a lot of things that you can get context from the mobile device, right? Like I can think about location, right? I can think about alerts that are coming from the platform because -- well, at the end of the day, that data is the same, right? It's coming from the MicroStrategy platform. So if something is triggered, you're going to get an alert on the model device. Again, it can also be contextual based on location, based on your interactions. It doesn't have to be a browser. Definitely, the experience is different, but this type of -- this concept can be applied also to mobile.

Makes sense.

Just to take a step back on that more generally with browsers and mobile apps. You don't necessarily -- you're not excluding the use of a browser if you're using a mobile app. Like you can embed mobile browsers within apps or you can actually have the entire apps that are just mobile web browsers themselves. So just to add a little bit more nuance to that point. Having an app doesn't necessarily exclude the browser usage as well.

Yes. I think it's a great point to make. All right. So we did get one more. So this is -- actually, we've got two more now. We'll take 2 more. So here we are. Second to last one, will MicroStrategy dossier ever be able to target widgets on other chapters or pages, right? So looking to click on Chapter 1 and it flows to Chapter 2, have a thought, but I will hand it over to Jose to answer this.

Yes. But if we can get like the person who asked a question, I would love to explore that use case. So maybe we can also follow up offline and see what are specific case. The answer is yes. But definitely I'm interested on the type of application that is being built.

Got it. And then I'll end on this question. I think it's an interesting one is, will we ever have Hyper and mobile browsers? Or how will that work? Can that work, right?

Currently, Hyper exists as an Android application and as an iOS application, and that's the strategy for mobile support for Hyper.

Got it. I actually have an interesting question just from my perspective is, Jose, do you ever see Hyper -- that Hyper app that we do have integrating with library mobile or something where you have dossiers and Hyper.

Completely. Actually, I think like the integration of Hypermobile with library is completely part of our vision. Now on the other thing, like if I can answer again the question, like as an extension the path is basically the native app. However, we talk also about Hyper as a [indiscernible] and on that one you don't have any of the extension. And at the end of the day, like you're still going to be accessing the site from your mobile browser. And if that website that you are accessing, it does have Hyper integrated, you're going to get hyper functionality.

Yes. All right. Awesome. So we will stop here. I don't want to make anyone miss any lunch plans, et cetera. But again, we will be having a lot of these webinars moving forward. So make sure to keep tuning in. We have great speakers. Jose and Rowan, thank you so much for your time, that was amazing. And I think we decided that the future is actionable, augmented and pervasive. Now I think that's across the board, what we are going to be doing.

Thank you, Holly.

Thank you so much.

Thank you everyone for joining, and we look forward to seeing you all soon.

Bye. Thanks, everybody.