[Music] as you heard over the course of our program organizations where more people are using analytics who have deeper capabilities in each of the four e's that's everyone everything everywhere and easy analytics those organizations achieve more roi from their respective investments in analytics and automation than those who don't we also heard a great story from ebay a great example of an enterprise that is truly democratizing analytics across its organization it's enabling an empowering line of business users to use analytics not only focus on key aspects of their job but develop new skills rather than doing the same repetitive tasks we want to thank you so much for watching the program today remember you can find all of the content on thecube.net you can find all of the news from today on siliconangle.com and of course alteryx.com we also want to thank alteryx for making this program possible and for sponsoring the cube for all of my guests i'm lisa martin i want to thank you for watching and bye for now [Music]

(light upbeat music) (mouse clicks) >> Hey, everyone. Welcome back to the program. Lisa Martin here. I've got two guests joining me. Please welcome back to The Cube, Paula Hansen, the chief revenue officer and president at Alteryx. And Jacqui Van der Leij - Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the program. >> Thank you, Lisa. >> Thank you, Lisa. >> It's great to be here. >> Yeah, Paula. We're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson, they talked about the need to democratize analytics across any organization to really drive innovation. With analytics as they talked about at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customer's success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform but ultimately, we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organizations scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. >> Excellent. Sounds like a very strategic program. We're going to unpack that. Jacqui let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How, Jacqui, did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is just when we started out was, is that, you know, our, especially in finance they became spreadsheet professionals, instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think, you know, eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is, is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no, we're not independent. You couldn't move forward. You would've been dependent on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. And finally, we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks because you always have, not always, but most of the times you have support from the top in our case, we have, but in the end of the day, it's our people that need to actually really embrace it and making that accessible for them, I would say is definitely not per se, a roadblock but basically some, a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula will start with you, and then Jacqui will go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data driven? Paula? >> Yes. Well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting, all of our key performance metrics for business planning across our audit function to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter so it's really remained across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases. And so one of the other things that we've seen many companies do is to gamify that process to build a game that brings users into the experience for training and to work with each other, to problem solve, and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported that they have access to the training that they need. And ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of you know, getting people excited about it but it's also understanding that this is a journey. And everybody is the different place in their journey. You have folks that's already really advanced who has done this every day, and then you have really some folks that this is brand new and, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the initial destination. I say initially, because I believe the journey is never really complete. What we have done is that we decided to invest in a... We build a proof of concepts and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom. And we told people, "Listen, we're going to teach you this tool, super easy. And let's just see what you can do." We ended up having 70 entries. We had only three weeks. So, and these are people that has... They do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon. From the 70 entries with people that have never, ever done anything like this before and there you had the result. And then it just went from there. It was people had a proof of concept, they knew that it worked, and they overcame that initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula will start with you. >> Absolutely. And Jacqui says it so well, which is that it really is a journey that organizations are on. And we, as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay, and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED, we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries. And we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED just made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kicked that momentum from the hackathon. Like we don't lose that excitement, right? So we just launched a program called eBay Masterminds. And what it basically is, it's an inclusive innovation initiative, where we firmly believe that innovation is for upscaling for all analytics role. So it doesn't matter your background, doesn't matter which function you are in, come and participate in this, where we really focus on innovation, introducing new technologies and upscaling our people. We are... Apart from that, we also said... Well, we should just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use alter Alteryx. And we're working with actually, we're working with SparkED and they're helping us develop that program. And we really hope that, let us say, by the end of the year have a pilot and then also next, was hoping to roll it out in multiple locations, in multiple countries, and really, really focus on that whole concept of analytics role. >> Analytics role, sounds like Alteryx and eBay have a great synergistic relationship there, that is jointly aimed at, especially, kind of, going down the stuff and getting people when they're younger interested and understanding how they can be empowered with data across any industry. Paula let's go back to you. You were recently on The Cube's Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world? How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last, I check there was 2 million data scientists in the world. So that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. (Paula clears throat) So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud, is to empower all of those people in every job function regardless of their skillset. As Jacqui pointed out from people that would, you know are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud and it operates in a multi-cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skills gap as you were saying, there's only 2 million data scientists. You don't need to be a data scientist. That's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues. And what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we started about getting excited about things when it comes to analytics, I can go on all day but I'll keep it short and sweet for you. I do think we are on the topic full of data scientists. And I really feel that that is your next step, for us anyways, it's just that, how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx would just release the AI/ML solution, allowing, you know, folks to not have a data scientist program but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses quite a few. And right now, through our mastermind program we're actually running a four-months program for all skill levels. Teaching them AI/ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services, we have even some of our engineers, are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all was able to develop a solution where, you know, there is a checkout feedback, checkout functionality on the eBay site, where sellers or buyers can verbatim add information. And she build a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we, as a human even step in. And now instead of us or somebody going to the bay to try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value. And it's a beautiful tool, and I'm very impressed when you saw the demo and they've been developing that further. >> That sounds fantastic. And I think just the one word that keeps coming to mind and we've said this a number of times in the program today is, empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you >> Thank you, Lisa. >> Thank you so much. (light upbeat music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four E's that's, everyone, everything, everywhere and easy analytics. Those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics. Not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com, and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring The Cube. For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (light upbeat music)

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all, as we know, data is changing the world, and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to the Cube's presentation of "Democratizing Analytics Across the Enterprise," made possible by Alteryx. An Alteryx-commissioned IDC InfoBrief entitled, Four Ways to Unlock Transformative Business Outcomes From Analytics Investments, found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special Cube presentation, Jason Klein, Product Marketing Director of Alteryx, will join me to share key findings from the new Alteryx-commissioned IDC Brief, and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, Chief Data and Analytics Officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then, in our final segment, Paula Hansen, who is the President and Chief Revenue Officer of Alteryx, and Jacqui Van der Leij-Greyling, who is the Global Head of Tax Technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, Product Marketing Director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research which spoke with about 1500 leaders? What nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees. And this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity, and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics. And we're able to focus on the behaviors driving higher ROI. >> So the InfoBrief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the InfoBrief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack what's driving this demand, this need for analytics across organizations? >> Sure, well, first, there's more data than ever before. The data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins, and to improve customer experiences. And analytics, along with automation and AI, is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> Yet not all analytics spending is resulting in the same ROI. So, what are some of the discrepancies that the InfoBrief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead, they're relying on outdated spreadsheet technology. Nine out of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically then, what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value >> from their data and analytics and achieved more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics, across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture, and this begins with people. But we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources compared to only 67% among the ROI laggards. >> So interesting that you mentioned people. I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand. We know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right. So analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also, among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well, compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively, and letting them do so cross-functionally >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side, and is expected to spend more on analytics than other IT. What risks does this present to the overall organization? If IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this is because the lines of business have recognized the value of analytics and plan to invest accordingly. But a lack of alignment between IT and business, this will negatively impact governance, which ultimately impedes democratization and hence, ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more, you know, on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up an Alteryx environment. But also to take a look at your analytics stack, and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process and technologies. Jason, thank you so much for joining me today, unpacking the IDC InfoBrief and the great nuggets in there. Lots that organizations can learn, and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you. It's been a pleasure. >> In a moment, Alan Jacobson, who's the Chief Data and Analytics Officer at Alteryx, is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching the Cube, the leader in tech enterprise coverage. (gentle music)

>>Hey, everyone. Welcome back to accelerating analytics, maturity. I'm your host. Lisa Martin, Alan Jacobson joins me next. The chief data and analytics officer at Altrix Ellen. It's great to have you on the program. >>Thanks Lisa. >>So Ellen, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics >>And you're spot on many organizations really aren't leveraging the, the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole, we just launched an assessment tool on our website that we built with the international Institute of analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >>So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >>So domain experts are really in the best position. They, they know where the gold is buried in their companies. They know where the inefficiencies are, and it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a, or a logistics expert of your company. It much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If, if you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional? If they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics, to stay current and, and be capable for their companies. And companies need people who can do that. >>Absolutely. It seems like it's table stakes. These days, let's look at different industries. Now, are there differences in how you see analytics in automation being employed in different industries? I know Altrix is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams, any differences in industries. >>Yeah. There's an incredible actually commonality between domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are, are much larger than you might think. And even on the, on, on the, on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use TRICS across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Altrics. And if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 sports has. And I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see fortune 500 finance departments doing to optimize their budget. And so really the, the commonality is very high. Even across industries. >>I bet every F fortune 500 or even every company would love to be compared to the same department within McLaren F1, just to know that wow, what they're doing is so in incre incredibly important as is what we are doing. Absolutely. So talk about lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature >>Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if, if your company isn't going on this journey and your competition is it, it can be a, a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment. And so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey. Can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies they didn't. And so picking technologies, that'll help everyone do this and, and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key, >>So faster able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >>Absolutely the IDC or not. The IDC, the international Institute of analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company. They showed correlation to revenue and they showed correlation to shareholder values. So across really all of the, the, the key measures of business, the more analytically mature companies simply outperformed their competition. >>And that's key these days is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I gotta ask you, is it really that easy for the line of business workers who aren't trained in data science, to be able to jump in, look at data, uncover and extract business insights to make decisions. >>So in, in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Altrics they're, Altrics certified. And, and it was quite easy. It took 'em about 20 hours and they were, they, they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant, that's been doing the best accounting work in your company for the last 20 years. And all you happen to know is a spreadsheet for those 20 years. Are you ready to learn some new skills? And, and I would suggest you probably need to, if you want, keep up with your profession. The, the big four accounting firms have trained over a hundred thousand people in Altrix just one firm has trained over a hundred thousand. >>You, you can't be an accountant or an auditor at some of these places with, without knowing Altrix. And so the hard part, really in the end, isn't the technology and learning analytics and data science. The harder part is this change management change is hard. I should probably eat better and exercise more, but it's, it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to, to help them become the digitally enabled accountant of the future. The, the logistics professional that is E enabled that that's the challenge. >>That's a huge challenge. Cultural, cultural shift is a challenge. As you said, change management. How, how do you advise customers? If you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >>Yeah, that's a great question. So, so people entering into the workforce today, many of them are starting to have these skills Altrics is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can, it can be great fun. We, we have a great time with, with many of the customers that we work with helping them, you know, do this, helping them go on the journey and the ROI, as I said, you know, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that really make great impact to society as a whole. >>Isn't that so fantastic to see the, the difference that that can make. It sounds like you're, you guys are doing a great job of democratizing access to alter X to everybody. We talked about the line of business folks and the incredible importance of enabling them and the, the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alter's customers that really show data breakthroughs by the lines of business using the technology? >>Yeah, absolutely. So, so many to choose from I'll I'll, I'll give you two examples. Quickly. One is armor express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We, we see how important the supply chain is. And so adjusting supply to, to match demand is, is really vital. And so they've used all tricks to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a, a dollar standpoint, they cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer customer demand. And so when people have orders and are, are looking to pick up a vest, they don't wanna wait. >>And, and it becomes really important to, to get that right. Another great example is British telecom. They're, they're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and, and this is crazy to think about over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and, and report, and obviously running 140 legacy models that had to be done in a certain order and linked incredibly challenging. It took them over four weeks, each time that they had to go through that process. And so to, to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Altrix and, and, and learn Altrix. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours. >>It took to run in a 60% runtime performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and past data into a spreadsheet. And that was just one project that this group of, of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in, in other areas, you can imagine the impact by the end of the year that they will have on their business, you know, potentially millions upon millions of dollars. This is what we see again. And again, company after company government agency, after government agency is how analytics are really transforming the way work is being done. >>That was the word that came to mind when you were describing the all three customer examples, the transformation, this is transformative. The ability to leverage alters to, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And, and also the business outcomes. You mentioned, those are substantial metrics based business outcomes. So the ROI and leveraging a technology like alri seems to be right there, sitting in front of you. >>That's right. And, and to be honest, it's not only important for these businesses. It's important for, for the knowledge workers themselves. I mean, we, we hear it from people that they discover Alrich, they automate a process. They finally get to get home for dinner with their families, which is fantastic, but, but it leads to new career paths. And so, you know, knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytics and analytic and automate processes actually matches the needs of the employees. And, you know, they too wanna learn these skills and become more advanced in their capabilities, >>Huge value there for the business, for the employees themselves to expand their skillset, to, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there. Alan, is there anywhere that you wanna point the audience to go, to learn more about how they can get started? >>Yeah. So one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who wanna experience Altrix, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning and, and see where you are on the journey and just reach out. You know, we'd love to work with you and your organization to see how we can help you accelerate your journey on, on analytics and automation, >>Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >>Thank you so much >>In a moment, Paula Hanson, who is the president and chief revenue officer of ultras and Jackie Vander lay graying. Who's the global head of tax technology at eBay will join me. You're watching the cube, the leader in high tech enterprise coverage.

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all, as we know, data is changing the world, and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to the Cube's presentation of "Democratizing Analytics Across the Enterprise," made possible by Alteryx. An Alteryx-commissioned IDC InfoBrief entitled, Four Ways to Unlock Transformative Business Outcomes From Analytics Investments, found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special Cube presentation, Jason Klein, Product Marketing Director of Alteryx, will join me to share key findings from the new Alteryx-commissioned IDC Brief, and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, Chief Data and Analytics Officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then, in our final segment, Paula Hansen, who is the President and Chief Revenue Officer of Alteryx, and Jacqui Van der Leij-Greyling, who is the Global Head of Tax Technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, Product Marketing Director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research which spoke with about 1500 leaders? What nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees. And this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity, and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics. And we're able to focus on the behaviors driving higher ROI. >> So the InfoBrief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the InfoBrief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack what's driving this demand, this need for analytics across organizations? >> Sure, well, first, there's more data than ever before. The data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins, and to improve customer experiences. And analytics, along with automation and AI, is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the InfoBrief uncovered with respect to the the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy, as compared to the technology itself. And next, while data is everywhere, most organizations, 63%, from our survey, are still not using the full breadth of data types available. Yet, data's never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytics tools to help everyone unlock the power of data. They instead rely on outdated spreadsheet technology. In our survey, 9 out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely, you can do so. Yep, we'll go back to Lisa's question. Let's retake the question and the answer. >> That'll be not all analog spending results in the same ROI. What are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we can get that clean question and answer. >> Okay. >> Thank you for that. on your ISO, we're still speeding, Lisa. So give it a beat in your head, and then on you. >> Yet not all analytics spending is resulting in the same ROI. So, what are some of the discrepancies that the InfoBrief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow, and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead, they're relying on outdated spreadsheet technology. Nine out of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone, regardless of skill level, should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically then, what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieved more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics, across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did. It did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads. Can I start that one over? Can I redo this one? >> Sure. >> Yeah >> Of course. Stand by. >> Tongue tied. >> Yep. No worries. >> One second. >> If we could get, if we could do the same, Lisa, just have a clean break. We'll go to your question. Yep. >> Yeah. >> On you Lisa. Just give that a count and whenever you're ready, here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture, and this begins with people. But we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources compared to only 67% among the ROI laggards. >> So interesting that you mentioned people. I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand. We know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right. So analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also, among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well, compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively, and letting them do so cross-functionally >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side, and is expected to spend more on analytics than other IT. What risks does this present to the overall organization? If IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this is because the lines of business have recognized the value of analytics and plan to invest accordingly. But a lack of alignment between IT and business, this will negatively impact governance, which ultimately impedes democratization and hence, ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more, you know, on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up an Alteryx environment. But also to take a look at your analytics stack, and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process and technologies. Jason, thank you so much for joining me today, unpacking the IDC InfoBrief and the great nuggets in there. Lots that organizations can learn, and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you. It's been a pleasure. >> In a moment, Alan Jacobson, who's the Chief Data and Analytics Officer at Alteryx, is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching the Cube, the leader in tech enterprise coverage. (gentle music)

>>Hey everyone. Welcome back to the program. Lisa Martin here, I've got two guests joining me, please. Welcome back to the cube. Paula Hansen, the chief revenue officer and president at Al alters and Jackie Vander lake grayling joins us as well. The global head of tax technology at eBay. They're gonna share with you how an alter Ricks is helping eBay innovate with analytics. Ladies. Welcome. It's great to have you both on the program. >>Thank you, Lisa. It's great to be here. >>Yeah, Paula, we're gonna start with you in this program. We've heard from Jason Klein, we've heard from Alan Jacobson, they talked about the need to democratize analytics across any organization to really drive innovation with analytics. As they talked about at the forefront of software investments, how's alters helping its customers to develop roadmaps for success with analytics. >>Well, thank you, Lisa. It absolutely is about our customer's success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course, with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics through things like enablement programs, skills, assessments, hackathons, setting up centers of excellence to help their organizations scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics, maturity curve with proven technologies and best practices so they can make better business decisions and compete in their respective industries. >>Excellent. Sounds like a very strategic program. We're gonna unpack that Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jackie did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >>So I think the main thing for us is just when we started out was is that, you know, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and be more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes, >>Starting with people is really critical. Jackie, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >>So I think, you know, eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and, and just finding those data sources and finding ways to connect to them to move forward. The other thing is, is that, you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And we, there was no, we're not independent. You couldn't move forward. You would've opinion on somebody else's roadmap to get to data and to get the information you wanted. So really finding something that everybody could access analytics or access data. >>And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy? And that is not so daunting on somebody who's brand new to the field. And I would, I would call those out as your, as your major roadblocks, because you always have not always, but most of the times you have support from the top in our case, we have, but in the end of the day, it's, it's our people that need to actually really embrace it and, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically some, a block you wanna be able to move. >>It's really all about putting people. First question for both of you and Paula will start with you. And then Jackie will go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data so that they can actually be data driven Paula. >>Yes. Well, we leverage our platform across all of our business functions here at Altrix and just like Jackie explained it, eBay finances is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Rubin has been a, a key sponsor for using our own technology. We use Altrix for forecasting, all of our key performance metrics for business planning across our audit function, to help with compliance and regulatory requirements tax, and even to close our books at the end of each quarter. So it's really remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? >>And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jackie mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need. And ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >>That confidence is key. Jackie, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >>Yeah, I think it means to what Paula has said in terms of, you know, you know, getting people excited about it, but it's also understanding that this is a journey and everybody's the different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new and, or maybe somewhere in between. And it's about how you put, get everybody in their different phases to get to the, the initial destination. I say initially, because I believe the journey is never really complete. What we have done is, is that we decided to invest in an Ebola group of concept. And we got our CFO to sponsor a hackathon. We opened it up to everybody in finance, in the middle of the pandemic. So everybody was on zoom and we had, and we told people, listen, we're gonna teach you this tool super easy. >>And let's just see what you can do. We ended up having 70 entries. We had only three weeks. So, and these are people that has N that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 inches with people that have never, ever done anything like this before and there you had the result. And then it just went from there. It was, people had a proof of concept. They, they knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up. Now >>That's fantastic. And the, the business outcome that you mentioned there, the business impact is massive helping folks get that confidence to be able to overcome. Sometimes the, the cultural barriers is key. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you are empowering the next generation of data workers, Paula will start with you? >>Absolutely. And, and Jackie says it so well, which is that it really is a journey that organizations are on. And, and we, as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Altrix to help address this skillset gap on a global level is through a program that we call sparked, which is essentially a, no-cost a no cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to, to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with sparked. We started last may, but we currently have over 850 educational institutions globally engaged across 47 countries. And we're gonna continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close gap and empower more people within necessary analytics skills to solve all the problems that data can help solve. >>So spark has made a really big impact in such a short time period. And it's gonna be fun to watch the progress of that. Jackie, let's go over to you now talk about some of the things that eBay is doing to empower the next generation of data workers. >>So we basically wanted to make sure that we keep that momentum from the hackathon that we don't lose that excitement, right? So we just launched a program called Ebo masterminds. And what it basically is, it's an inclusive innovation initiative where we firmly believe that innovation is all up scaling for all analytics for. So it doesn't matter. Your background doesn't matter which function you are in, come and participate in, in this where we really focus on innovation, introducing new technologies and upskilling our people. We are apart from that, we also say, well, we should just keep it to inside eBay. We, we have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use alter alter. And we're working with actually, we're working with spark and they're helping us develop that program. And we really hope that as a say, by the end of the year, have a pilot and then also make you, so we roll it out in multiple locations in multiple countries and really, really focus on, on that whole concept of analytics, role >>Analytics for all sounds like ultra and eBay have a great synergistic relationship there that is jointly aimed at, especially kind of going down the staff and getting people when they're younger, interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you. You were recently on the Cube's super cloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating. What is by default a multi-cloud world? How does the alters analytics cloud platform enable CIOs to democratize analytics across their organization? >>Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I check there was 2 million data scientists in the world. So that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs with business leaders is that they're integrating data analysis and the skill of data analysis into virtually every job function. And that is what we think of when we think of analytics for all. And so our mission with Altrics analytics cloud is to empower all of those people in every job function, regardless of their skillset. As Jackie pointed out from people that would, you know, are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Altrics analytics cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and drive real business outcomes. As a result of unlocking the potential of data, >>As well as really re lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist. That's the, the beauty of what Altrics is enabling. And, and eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where alters fits in on as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >>When we start about getting excited about things, when it comes to analytics, I can go on all day, but I I'll keep it short and sweet for you. I do think we are on the topic full of, of, of data scientists. And I really feel that that is your next step for us anyways, is that, how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's, it's something completely different. And it's something that, that is in everybody to a certain extent. So again, partner with three X would just released the AI ML solution, allowing, you know, folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with alters and we, we purchased a license, this quite a few. And right now through our mastermind program, we're actually running a four months program for all skill levels, teaching, teaching them AI ML and machine learning and how they can build their own models. >>We are really excited about that. We have over 50 participants without the background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I wanna give you a quick example of, of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where, you know, there is a checkout feedback checkout functionality on the eBay site where sellers or buyers can verbatim add information. And she build a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we, as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value. >>And it's a beautiful tool and very impressed. You saw the demo and they developing that further. >>That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with, with varying degrees of skill level, going down to the high school level, really exciting, we'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I wanna thank you so much for joining me on the program today and talking about how alters and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >>Thank you. >>As you heard over the course of our program organizations, where more people are using analytics who have the deeper capabilities in each of the four E's, that's, everyone, everything everywhere and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling an empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We wanna thank you so much for watching the program today. Remember you can find all of the content on the cue.net. You can find all of the news from today on Silicon angle.com and of course, alter.com. We also wanna thank alt alters for making this program possible and for sponsored in the queue for all of my guests. I'm Lisa Martin. We wanna thank you for watching and bye for now.

>> It's no surprise that 73% of organizations indicate analytics spend will outpace other software investments in the next 12 to 18 months. After all as we know, data is changing the world and the world is changing with it. But is everyone's spending resulting in the same ROI? This is Lisa Martin. Welcome to "theCUBE"'s presentation of democratizing analytics across the enterprise, made possible by Alteryx. An Alteryx commissioned IDC info brief entitled, "Four Ways to Unlock Transformative Business Outcomes from Analytics Investments" found that 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. On this special "CUBE" presentation, Jason Klein, product marketing director of Alteryx, will join me to share key findings from the new Alteryx commissioned IDC brief and uncover how enterprises can derive more value from their data. In our second segment, we'll hear from Alan Jacobson, chief data and analytics officer at Alteryx. He's going to discuss how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. And then in our final segment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who is the global head of tax technology at eBay, they'll join me. They're going to share how Alteryx is helping the global eCommerce company innovate with analytics. Let's get the show started. (upbeat music) Jason Klein joins me next, product marketing director at Alteryx. Jason, welcome to the program. >> Hello, nice to be here. >> Excited to talk with you. What can you tell me about the new Alteryx IDC research, which spoke with about 1500 leaders, what nuggets were in there? >> Well, as the business landscape changes over the next 12 to 18 months, we're going to see that analytics is going to be a key component to navigating this change. 73% of the orgs indicated that analytics spend will outpace other software investments. But just putting more money towards technology, it isn't going to solve everything. And this is why everyone's spending is resulting in different ROIs. And one of the reasons for this gap is because 93% of organizations, they're still not fully using the analytics skills of their employees, and this widening analytics gap, it's threatening operational progress by wasting workers' time, harming business productivity and introducing costly errors. So in this research, we developed a framework of enterprise analytics proficiency that helps organizations reap greater benefits from their investments. And we based this framework on the behaviors of organizations that saw big improvements across financial, customer, and employee metrics, and we're able to focus on the behaviors driving higher ROI. >> So the info brief also revealed that nearly all organizations are planning to increase their analytics spend. And it looks like from the info brief that nearly three quarters plan on spending more on analytics than any other software. And can you unpack, what's driving this demand, this need for analytics across organizations? >> Sure, well first there's more data than ever before, the data's changing the world, and the world is changing data. Enterprises across the world, they're accelerating digital transformation to capitalize on new opportunities, to grow revenue, to increase margins and to improve customer experiences. And analytics along with automation and AI is what's making digital transformation possible. They're providing the fuel to new digitally enabled lines of business. >> One of the things that the study also showed was that not all analytics spending is resulting in the same ROI. What are some of the discrepancies that the info brief uncovered with respect to the changes in ROI that organizations are achieving? >> Our research with IDC revealed significant roadblocks across people, processes, and technologies. They're preventing companies from reaping greater benefits from their investments. So for example, on the people side, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% from our survey, are still not using the full breadth of data types available. Yet data's never been this prolific, it's going to continue to grow, and orgs should be using it to their advantage. And lastly organizations, they need to provide the right analytics tools to help everyone unlock the power of data. >> So they- >> They instead rely on outdated spreadsheet technology. In our survey, nine out of 10 respondents said less than half of their knowledge workers are active users of analytics software beyond spreadsheets. But true analytic transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and be driving value. >> Should we retake that, since I started talking over Jason accidentally? >> Yep, absolutely we can do so. We'll just go, yep, we'll go back to Lisa's question. Let's just, let's do the, retake the question and the answer, that'll be able to. >> It'll be not all analytics spending results in the same ROI, what are some of the discrepancies? >> Yes, Lisa, so we'll go from your ISO, just so we get that clean question and answer. >> Okay. >> Thank you for that. On your ISO, we're still speeding, Lisa, so give it a beat in your head and then on you. >> Yet not all analytics spending is resulting in the same ROI. So what are some of the discrepancies that the info brief uncovered with respect to ROI? >> Well, our research with IDC revealed significant roadblocks across people, processes, and technologies, all preventing companies from reaping greater benefits from their investments. So on the people side, for example, only one out of five organizations reported a commensurate investment in upskilling for analytics and data literacy as compared to the technology itself. And next, while data is everywhere, most organizations, 63% in our survey, are still not using the full breadth of data types available. Data has never been this prolific. It's going to continue to grow and orgs should be using it to their advantage. And lastly, organizations, they need to provide the right analytic tools to help everyone unlock the power of data, yet instead they're relying on outdated spreadsheet technology. Nine of 10 survey respondents said that less than half of their knowledge workers are active users of analytics software. True analytics transformation can't happen for an organization in a few select pockets or silos. We believe everyone regardless of skill level should be able to participate in the data and analytics process and drive value. >> So if I look at this holistically, then what would you say organizations need to do to make sure that they're really deriving value from their investments in analytics? >> Yeah, sure. So overall, the enterprises that derive more value from their data and analytics and achieve more ROI, they invested more aggressively in the four dimensions of enterprise analytics proficiency. So they've invested in the comprehensiveness of analytics across all data sources and data types, meaning they're applying analytics to everything. They've invested in the flexibility of analytics across deployment scenarios and departments, meaning they're putting analytics everywhere. They've invested in the ubiquity of analytics and insights for every skill level, meaning they're making analytics for everyone. And they've invested in the usability of analytics software, meaning they're prioritizing easy technology to accelerate analytics democratization. >> So very strategic investments. Did the survey uncover any specific areas where most companies are falling short, like any black holes that organizations need to be aware of at the outset? >> It did, it did. So organizations, they need to build a data-centric culture. And this begins with people. But what the survey told us is that the people aspect of analytics is the most heavily skewed towards low proficiency. In order to maximize ROI, organizations need to make sure everyone in the organization has access to the data and analytics technology they need. And then the organizations also have to align their investments with upskilling in data literacy to enjoy that higher ROI. Companies who did so experience higher ROI than companies who underinvested in analytics literacy. So among the high ROI achievers, 78% have a good or great alignment between analytics investment and workforce upskilling compared to only 64% among those without positive ROI. And as more orgs adopt cloud data warehouses or cloud data lakes, in order to manage the massively increasing workloads- Can I start that one over. >> Sure. >> Can I redo this one? >> Yeah. >> Of course, stand by. >> Tongue tied. >> Yep, no worries. >> One second. >> If we could do the same, Lisa, just have a clean break, we'll go your question. >> Yep, yeah. >> On you Lisa. Just give that a count and whenever you're ready. Here, I'm going to give us a little break. On you Lisa. >> So are there any specific areas that the survey uncovered where most companies are falling short? Like any black holes organizations need to be aware of from the outset? >> It did. You need to build a data-centric culture and this begins with people, but we found that the people aspect of analytics is most heavily skewed towards low proficiency. In order to maximize ROI organizations need to make sure everyone has access to the data and analytics technology they need. Organizations that align their analytics investments with upskilling enjoy higher ROI than orgs that are less aligned. For example, among the high ROI achievers in our survey, 78% had good or great alignment between analytics investments and workforce upskilling, compared to only 64% among those without positive ROI. And as more enterprises adopt cloud data warehouses or cloud data lakes to manage increasingly massive data sets, analytics needs to exist everywhere, especially for those cloud environments. And what we found is organizations that use more data types and more data sources generate higher ROI from their analytics investments. Among those with improved customer metrics, 90% were good or great at utilizing all data sources, compared to only 67% among the ROI laggards. >> So interesting that you mentioned people, I'm glad that you mentioned people. Data scientists, everybody talks about data scientists. They're in high demand, we know that, but there aren't enough to meet the needs of all enterprises. So given that discrepancy, how can organizations fill the gap and really maximize the investments that they're making in analytics? >> Right, so analytics democratization, it's no longer optional, but it doesn't have to be complex. So we at Alteryx, we're democratizing analytics by empowering every organization to upskill every worker into a data worker. And the data from this survey shows this is the optimal approach. Organizations with a higher percentage of knowledge workers who are actively using analytics software enjoy higher returns from their analytics investment than orgs still stuck on spreadsheets. Among those with improved financial metrics, AKA the high ROI achievers, nearly 70% say that at least a quarter of their knowledge workers are using analytics software other than spreadsheets compared to only 56% in the low ROI group. Also among the high ROI performers, 63% said data and analytic workers collaborate well or extremely well compared to only 51% in the low ROI group. The data from the survey shows that supporting more business domains with analytics and providing cross-functional analytics correlates with higher ROI. So to maximize ROI, orgs should be transitioning workers from spreadsheets to analytics software. They should be letting them collaborate effectively and letting them do so cross-functionally. >> Yeah, that cross-functional collaboration is essential for anyone in any organization and in any discipline. Another key thing that jumped out from the survey was around shadow IT. The business side is using more data science tools than the IT side. And it's expected to spend more on analytics than other IT. What risks does this present to the overall organization, if IT and the lines of business guys and gals aren't really aligned? >> Well, there needs to be better collaboration and alignment between IT and the line of business. The data from the survey, however, shows that business managers, they're expected to spend more on analytics and use more analytics tools than IT is aware of. And this isn't because the lines of business have recognized the value of analytics and plan to invest accordingly, but a lack of alignment between IT and business. This will negatively impact governance, which ultimately impedes democratization and hence ROI. >> So Jason, where can organizations that are maybe at the outset of their analytics journey, or maybe they're in environments where there's multiple analytics tools across shadow IT, where can they go to Alteryx to learn more about how they can really simplify, streamline, and dial up the value on their investment? >> Well, they can learn more on our website. I also encourage them to explore the Alteryx community, which has lots of best practices, not just in terms of how you do the analytics, but how you stand up in Alteryx environment, but also to take a look at your analytics stack and prioritize technologies that can snap to and enhance your organization's governance posture. It doesn't have to change it, but it should be able to align to and enhance it. >> And of course, as you mentioned, it's about people, process, and technologies. Jason, thank you so much for joining me today, unpacking the IDC info brief and the great nuggets in there. Lots that organizations can learn and really become empowered to maximize their analytics investments. We appreciate your time. >> Thank you, it's been a pleasure. >> In a moment, Alan Jacobson, who's the chief data and analytics officer at Alteryx is going to join me. He's going to be here to talk about how organizations across all industries can accelerate their analytic maturity to drive transformational business outcomes. You're watching "theCUBE", the leader in tech enterprise coverage. >> Somehow many have come to believe that data analytics is for the few, for the scientists, the PhDs, the MBAs. Well, it is for them, but that's not all. You don't have to have an advanced degree to do amazing things with data. You don't even have to be a numbers person. You can be just about anything. A titan of industry or a future titan of industry. You could be working to change the world, your neighborhood, or the course of your business. You can be saving lives or just looking to save a little time. The power of data analytics shouldn't be limited to certain job titles or industries or organizations because when more people are doing more things with data, more incredible things happen. Analytics makes us smarter and faster and better at what we do. It's practically a superpower. That's why we believe analytics is for everyone, and everything, and should be everywhere. That's why we believe in analytics for all. (upbeat music) >> Hey, everyone. Welcome back to "Accelerating Analytics Maturity". I'm your host, Lisa Martin. Alan Jacobson joins me next. The chief of data and analytics officer at Alteryx. Alan, it's great to have you on the program. >> Thanks, Lisa. >> So Alan, as we know, everyone knows that being data driven is very important. It's a household term these days, but 93% of organizations are not utilizing the analytics skills of their employees, which is creating a widening analytics gap. What's your advice, your recommendations for organizations who are just starting out with analytics? >> You're spot on, many organizations really aren't leveraging the full capability of their knowledge workers. And really the first step is probably assessing where you are on the journey, whether that's you personally, or your organization as a whole. We just launched an assessment tool on our website that we built with the International Institute of Analytics, that in a very short period of time, in about 15 minutes, you can go on and answer some questions and understand where you sit versus your peer set versus competitors and kind of where you are on the journey. >> So when people talk about data analytics, they often think, ah, this is for data science experts like people like you. So why should people in the lines of business like the finance folks, the marketing folks, why should they learn analytics? >> So domain experts are really in the best position. They know where the gold is buried in their companies. They know where the inefficiencies are. And it is so much easier and faster to teach a domain expert a bit about how to automate a process or how to use analytics than it is to take a data scientist and try to teach them to have the knowledge of a 20 year accounting professional or a logistics expert of your company. Much harder to do that. And really, if you think about it, the world has changed dramatically in a very short period of time. If you were a marketing professional 30 years ago, you likely didn't need to know anything about the internet, but today, do you know what you would call that marketing professional if they didn't know anything about the internet, probably unemployed or retired. And so knowledge workers are having to learn more and more skills to really keep up with their professions. And analytics is really no exception. Pretty much in every profession, people are needing to learn analytics to stay current and be capable for their companies. And companies need people who can do that. >> Absolutely, it seems like it's table stakes these days. Let's look at different industries now. Are there differences in how you see analytics in automation being employed in different industries? I know Alteryx is being used across a lot of different types of organizations from government to retail. I also see you're now with some of the leading sports teams. Any differences in industries? >> Yeah, there's an incredible actually commonality between the domains industry to industry. So if you look at what an HR professional is doing, maybe attrition analysis, it's probably quite similar, whether they're in oil and gas or in a high tech software company. And so really the similarities are much larger than you might think. And even on the sports front, we see many of the analytics that sports teams perform are very similar. So McLaren is one of the great partners that we work with and they use Alteryx across many areas of their business from finance to production, extreme sports, logistics, wind tunnel engineering, the marketing team analyzes social media data, all using Alteryx, and if I take as an example, the finance team, the finance team is trying to optimize the budget to make sure that they can hit the very stringent targets that F1 Sports has, and I don't see a ton of difference between the optimization that they're doing to hit their budget numbers and what I see Fortune 500 finance departments doing to optimize their budget, and so really the commonality is very high, even across industries. >> I bet every Fortune 500 or even every company would love to be compared to the same department within McLaren F1. Just to know that wow, what they're doing is so incredibly important as is what we're doing. >> So talk- >> Absolutely. >> About lessons learned, what lessons can business leaders take from those organizations like McLaren, who are the most analytically mature? >> Probably first and foremost, is that the ROI with analytics and automation is incredibly high. Companies are having a ton of success. It's becoming an existential threat to some degree, if your company isn't going on this journey and your competition is, it can be a huge problem. IDC just did a recent study about how companies are unlocking the ROI using analytics. And the data was really clear, organizations that have a higher percentage of their workforce using analytics are enjoying a much higher return from their analytic investment, and so it's not about hiring two double PhD statisticians from Oxford. It really is how widely you can bring your workforce on this journey, can they all get 10% more capable? And that's having incredible results at businesses all over the world. An another key finding that they had is that the majority of them said that when they had many folks using analytics, they were going on the journey faster than companies that didn't. And so picking technologies that'll help everyone do this and do this fast and do it easily. Having an approachable piece of software that everyone can use is really a key. >> So faster, able to move faster, higher ROI. I also imagine analytics across the organization is a big competitive advantage for organizations in any industry. >> Absolutely the IDC, or not the IDC, the International Institute of Analytics showed huge correlation between companies that were more analytically mature versus ones that were not. They showed correlation to growth of the company, they showed correlation to revenue and they showed correlation to shareholder values. So across really all of the key measures of business, the more analytically mature companies simply outperformed their competition. >> And that's key these days, is to be able to outperform your competition. You know, one of the things that we hear so often, Alan, is people talking about democratizing data and analytics. You talked about the line of business workers, but I got to ask you, is it really that easy for the line of business workers who aren't trained in data science to be able to jump in, look at data, uncover and extract business insights to make decisions? >> So in many ways, it really is that easy. I have a 14 and 16 year old kid. Both of them have learned Alteryx, they're Alteryx certified and it was quite easy. It took 'em about 20 hours and they were off to the races, but there can be some hard parts. The hard parts have more to do with change management. I mean, if you're an accountant that's been doing the best accounting work in your company for the last 20 years, and all you happen to know is a spreadsheet for those 20 years, are you ready to learn some new skills? And I would suggest you probably need to, if you want to keep up with your profession. The big four accounting firms have trained over a hundred thousand people in Alteryx. Just one firm has trained over a hundred thousand. You can't be an accountant or an auditor at some of these places without knowing Alteryx. And so the hard part, really in the end, isn't the technology and learning analytics and data science, the harder part is this change management, change is hard. I should probably eat better and exercise more, but it's hard to always do that. And so companies are finding that that's the hard part. They need to help people go on the journey, help people with the change management to help them become the digitally enabled accountant of the future, the logistics professional that is E enabled, that's the challenge. >> That's a huge challenge. Cultural shift is a challenge, as you said, change management. How do you advise customers if you might be talking with someone who might be early in their analytics journey, but really need to get up to speed and mature to be competitive, how do you guide them or give them recommendations on being able to facilitate that change management? >> Yeah, that's a great question. So people entering into the workforce today, many of them are starting to have these skills. Alteryx is used in over 800 universities around the globe to teach finance and to teach marketing and to teach logistics. And so some of this is happening naturally as new workers are entering the workforce, but for all of those who are already in the workforce, have already started their careers, learning in place becomes really important. And so we work with companies to put on programmatic approaches to help their workers do this. And so it's, again, not simply putting a box of tools in the corner and saying free, take one. We put on hackathons and analytic days, and it can be great fun. We have a great time with many of the customers that we work with, helping them do this, helping them go on the journey, and the ROI, as I said, is fantastic. And not only does it sometimes affect the bottom line, it can really make societal changes. We've seen companies have breakthroughs that have really made great impact to society as a whole. >> Isn't that so fantastic, to see the difference that that can make. It sounds like you guys are doing a great job of democratizing access to Alteryx to everybody. We talked about the line of business folks and the incredible importance of enabling them and the ROI, the speed, the competitive advantage. Can you share some specific examples that you think of Alteryx customers that really show data breakthroughs by the lines of business using the technology? >> Yeah, absolutely, so many to choose from. I'll give you two examples quickly. One is Armor Express. They manufacture life saving equipment, defensive equipments, like armor plated vests, and they were needing to optimize their supply chain, like many companies through the pandemic. We see how important the supply chain is. And so adjusting supply to match demand is really vital. And so they've used Alteryx to model some of their supply and demand signals and built a predictive model to optimize the supply chain. And it certainly helped out from a dollar standpoint. They cut over a half a million dollars of inventory in the first year, but more importantly, by matching that demand and supply signal, you're able to better meet customer demand. And so when people have orders and are looking to pick up a vest, they don't want to wait. And it becomes really important to get that right. Another great example is British Telecom. They're a company that services the public sector. They have very strict reporting regulations that they have to meet and they had, and this is crazy to think about, over 140 legacy spreadsheet models that they had to run to comply with these regulatory processes and report, and obviously running 140 legacy models that had to be done in a certain order and length, incredibly challenging. It took them over four weeks each time that they had to go through that process. And so to save time and have more efficiency in doing that, they trained 50 employees over just a two week period to start using Alteryx and learn Alteryx. And they implemented an all new reporting process that saw a 75% reduction in the number of man hours it took to run in a 60% run time performance. And so, again, a huge improvement. I can imagine it probably had better quality as well, because now that it was automated, you don't have people copying and pasting data into a spreadsheet. And that was just one project that this group of folks were able to accomplish that had huge ROI, but now those people are moving on and automating other processes and performing analytics in other areas. So you can imagine the impact by the end of the year that they will have on their business, potentially millions upon millions of dollars. And this is what we see again and again, company after company, government agency after government agency, is how analytics are really transforming the way work is being done. >> That was the word that came to mind when you were describing the all three customer examples, transformation, this is transformative. The ability to leverage Alteryx, to truly democratize data and analytics, give access to the lines of business is transformative for every organization. And also the business outcome you mentioned, those are substantial metrics based business outcomes. So the ROI in leveraging a technology like Alteryx seems to be right there, sitting in front of you. >> That's right, and to be honest, it's not only important for these businesses. It's important for the knowledge workers themselves. I mean, we hear it from people that they discover Alteryx, they automate a process, they finally get to get home for dinner with their families, which is fantastic, but it leads to new career paths. And so knowledge workers that have these added skills have so much larger opportunity. And I think it's great when the needs of businesses to become more analytic and automate processes actually matches the needs of the employees, and they too want to learn these skills and become more advanced in their capabilities. >> Huge value there for the business, for the employees themselves to expand their skillset, to really open up so many opportunities for not only the business to meet the demands of the demanding customer, but the employees to be able to really have that breadth and depth in their field of service. Great opportunities there, Alan. Is there anywhere that you want to point the audience to go to learn more about how they can get started? >> Yeah, so one of the things that we're really excited about is how fast and easy it is to learn these tools. So any of the listeners who want to experience Alteryx, they can go to the website, there's a free download on the website. You can take our analytic maturity assessment, as we talked about at the beginning, and see where you are on the journey and just reach out. We'd love to work with you and your organization to see how we can help you accelerate your journey on analytics and automation. >> Alan, it was a pleasure talking to you about democratizing data and analytics, the power in it for organizations across every industry. We appreciate your insights and your time. >> Thank you so much. >> In a moment, Paula Hansen, who is the president and chief revenue officer of Alteryx, and Jacqui Van der Leij Greyling, who's the global head of tax technology at eBay, will join me. You're watching "theCUBE", the leader in high tech enterprise coverage. >> 1200 hours of wind tunnel testing, 30 million race simulations, 2.4 second pit stops. >> Make that 2.3. >> Sector times out the wazoo. >> Way too much of this. >> Velocities, pressures, temperatures, 80,000 components generating 11.8 billion data points and one analytics platform to make sense of it all. When McLaren needs to turn complex data into winning insights, they turn to Alteryx. Alteryx, analytics automation. (upbeat music) >> Hey, everyone, welcome back to the program. Lisa Martin here, I've got two guests joining me. Please welcome back to "theCUBE" Paula Hansen, the chief revenue officer and president at Alteryx, and Jacqui Van der Leij Greyling joins us as well, the global head of tax technology at eBay. They're going to share with you how Alteryx is helping eBay innovate with analytics. Ladies, welcome, it's great to have you both on the program. >> Thank you, Lisa, it's great to be here. >> Yeah, Paula, we're going to start with you. In this program, we've heard from Jason Klein, we've heard from Alan Jacobson. They talked about the need to democratize analytics across any organization to really drive innovation. With analytics, as they talked about, at the forefront of software investments, how's Alteryx helping its customers to develop roadmaps for success with analytics? >> Well, thank you, Lisa. It absolutely is about our customers' success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts of course with our innovative technology and platform, but ultimately we help our customers to create a culture of data literacy and analytics from the top of the organization, starting with the C-suite. And we partner with our customers to build their roadmaps for scaling that culture of analytics, through things like enablement programs, skills assessments, hackathons, setting up centers of excellence to help their organization scale and drive governance of this analytics capability across the enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practices, so they can make better business decisions and compete in their respective industries. >> Excellent, sounds like a very strategic program, we're going to unpack that. Jacqui, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the IDC report that showed that 93% of organizations are not utilizing the analytics skills of their employees, but then there's eBay. How Jacqui did eBay become one of the 7% of organizations who's really maturing and how are you using analytics across the organization at eBay? >> So I think the main thing for us is when we started out was is that, our, especially in finance, they became spreadsheet professionals instead of the things that we really want our employees to add value to. And we realized we had to address that. And we also knew we couldn't wait for all our data to be centralized until we actually start using the data or start automating and being more effective. So ultimately we really started very, very actively embedding analytics in our people and our data and our processes. >> Starting with people is really critical. Jacqui, continuing with you, what were some of the roadblocks to analytics adoption that you faced and how did you overcome them? >> So I think eBay is a very data driven company. We have a lot of data. I think we are 27 years around this year, so we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them to move forward. The other thing is that people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals. And there was no, we were not independent. You couldn't move forward, you would've put it on somebody else's roadmap to get the data and to get the information if you want it. So really finding something that everybody could access analytics or access data. And finally we have to realize is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy, and that is not so daunting on somebody who's brand new to the field? And I would call those out as your major roadblocks, because you always have, not always, but most of the times you have support from the top, and in our case we have, but at the end of the day, it's our people that need to actually really embrace it, and making that accessible for them, I would say is definitely not per se, a roadblock, but basically a block you want to be able to move. >> It's really all about putting people first. Question for both of you, and Paula we'll start with you, and then Jacqui we'll go to you. I think the message in this program that the audience is watching with us is very clear. Analytics is for everyone, should be for everyone. Let's talk now about how both of your organizations are empowering people, those in the organization that may not have technical expertise to be able to leverage data, so that they can actually be data driven. Paula. >> Yes, well, we leverage our platform across all of our business functions here at Alteryx. And just like Jacqui explained, at eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jacqui mentioned, we have this huge amount of data flowing through our enterprise and the opportunity to leverage that into insights and analytics is really endless. So our CFO Kevin Rubin has been a key sponsor for using our own technology. We use Alteryx for forecasting all of our key performance metrics, for business planning, across our audit function, to help with compliance and regulatory requirements, tax, and even to close our books at the end of each quarter. So it's really going to remain across our business. And at the end of the day, it comes to how do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other, to problem solve and along the way, maybe earn badges depending on the capabilities and trainings that they take. And just have a little healthy competition as an employee base around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jacqui mentioned, it's really about ensuring that people feel comfortable, that they feel supported, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >> That confidence is key. Jacqui, talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >> Yeah, I think it means to what Paula has said in terms of getting people excited about it, but it's also understanding that this is a journey and everybody is at a different place in their journey. You have folks that's already really advanced who has done this every day. And then you have really some folks that this is brand new or maybe somewhere in between. And it's about how you get everybody in their different phases to get to the initial destination. I say initial, because I believe a journey is never really complete. What we have done is that we decided to invest, and built a proof of concept, and we got our CFO to sponsor a hackathon. We opened it up to everybody in finance in the middle of the pandemic. So everybody was on Zoom and we told people, listen, we're going to teach you this tool, it's super easy, and let's just see what you can do. We ended up having 70 entries. We had only three weeks. So and these are people that do not have a background. They are not engineers, they're not data scientists. And we ended up with a 25,000 hour savings at the end of that hackathon from the 70 entries with people that have never, ever done anything like this before. And there you have the result. And then it just went from there. People had a proof of concept. They knew that it worked and they overcame the initial barrier of change. And that's where we are seeing things really, really picking up now. >> That's fantastic. And the business outcome that you mentioned there, the business impact is massive, helping folks get that confidence to be able to overcome sometimes the cultural barriers is key here. I think another thing that this program has really highlighted is there is a clear demand for data literacy in the job market, regardless of organization. Can each of you share more about how you're empowering the next generation of data workers? Paula, we'll start with you. >> Absolutely, and Jacqui says it so well, which is that it really is a journey that organizations are on and we as people in society are on in terms of upskilling our capabilities. So one of the things that we're doing here at Alteryx to help address this skillset gap on a global level is through a program that we call SparkED, which is essentially a no-cost analytics education program that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this program's really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with SparkED. We started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises, when we close the gap and empower more people with the necessary analytics skills to solve all the problems that data can help solve. >> So SparkED has made a really big impact in such a short time period. It's going to be fun to watch the progress of that. Jacqui, let's go over to you now. Talk about some of the things that eBay is doing to empower the next generation of data workers. >> So we basically wanted to make sure that we kept that momentum from the hackathon, that we don't lose that excitement. So we just launched the program called eBay Masterminds. And what it basically is, is it's an inclusive innovation in each other, where we firmly believe that innovation is for upskilling for all analytics roles. So it doesn't matter your background, doesn't matter which function you are in, come and participate in in this where we really focus on innovation, introducing new technologies and upskilling our people. We are, apart from that, we also said, well, we shouldn't just keep it to inside eBay. We have to share this innovation with the community. So we are actually working on developing an analytics high school program, which we hope to pilot by the end of this year, where we will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, but also how to use Alteryx. And we're working with, actually, we're working with SparkED and they're helping us develop that program. And we really hope that at, say, by the end of the year, we have a pilot and then also next year, we want to roll it out in multiple locations in multiple countries and really, really focus on that whole concept of analytics for all. >> Analytics for all, sounds like Alteryx and eBay have a great synergistic relationship there that is jointly aimed at especially going down the stuff and getting people when they're younger interested, and understanding how they can be empowered with data across any industry. Paula, let's go back to you, you were recently on "theCUBE"'s Supercloud event just a couple of weeks ago. And you talked about the challenges the companies are facing as they're navigating what is by default a multi-cloud world. How does the Alteryx Analytics Cloud platform enable CIOs to democratize analytics across their organization? >> Yes, business leaders and CIOs across all industries are realizing that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organizations. Last I checked, there was 2 million data scientists in the world, so that's woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CIOs, with business leaders is that they're integrating data analysis and the skillset of data analysis into virtually every job function, and that is what we think of when we think of analytics for all. And so our mission with Alteryx Analytics Cloud is to empower all of those people in every job function, regardless of their skillset, as Jacqui pointed out from people that are just getting started all the way to the most sophisticated of technical users. Every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organizations. So that's our goal with Alteryx Analytics Cloud, and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyze, and report out so that we can break down data silos across the enterprise and help drive real business outcomes as a result of unlocking the potential of data. >> As well as really lessening that skill gap. As you were saying, there's only 2 million data scientists. You don't need to be a data scientist, that's the beauty of what Alteryx is enabling and eBay is a great example of that. Jacqui, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where Alteryx fits in as that analytics maturity journey continues and what are some of the things that you are most excited about as analytics truly gets democratized across eBay? >> When we're starting up and getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. I do think we are on the top of the pool of data scientists. And I really feel that that is your next step, for us anyways, is that how do we get folks to not see data scientists as this big thing, like a rocket scientist, it's something completely different. And it's something that is in everybody in a certain extent. So again, partnering with Alteryx who just released the AI ML solution, allowing folks to not have a data scientist program, but actually build models and be able to solve problems that way. So we have engaged with Alteryx and we purchased the licenses, quite a few. And right now through our Masterminds program, we're actually running a four month program for all skill levels, teaching them AI ML and machine learning and how they can build their own models. We are really excited about that. We have over 50 participants without a background from all over the organization. We have members from our customer services. We have even some of our engineers are actually participating in the program. We just kicked it off. And I really believe that that is our next step. I want to give you a quick example of the beauty of this is where we actually just allow people to go out and think about ideas and come up with things. And one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution where there is a checkout feedback functionality on the eBay side where sellers or buyers can verbatim add information. And she built a model to be able to determine what relates to tax specific, what is the type of problem, and even predict how that problem can be solved before we as a human even step in, and now instead of us or somebody going to verbatim and try to figure out what's going on there, we can focus on fixing the error versus actually just reading through things and not adding any value, and it's a beautiful tool and I was very impressed when I saw the demo and definitely developing that sort of thing. >> That sounds fantastic. And I think just the one word that keeps coming to mind, and we've said this a number of times in the program today is empowerment. What you're actually really doing to truly empower people across the organization with varying degrees of skill level, going down to the high school level, really exciting. We'll have to stay tuned to see what some of the great things are that come from this continued partnership. Ladies, I want to thank you so much for joining me on the program today and talking about how Alteryx and eBay are really partnering together to democratize analytics and to facilitate its maturity. It's been great talking to you. >> Thank you, Lisa. >> Thank you so much. (cheerful electronic music) >> As you heard over the course of our program, organizations where more people are using analytics who have deeper capabilities in each of the four Es, that's everyone, everything, everywhere, and easy analytics, those organizations achieve more ROI from their respective investments in analytics and automation than those who don't. We also heard a great story from eBay, great example of an enterprise that is truly democratizing analytics across its organization. It's enabling and empowering line of business users to use analytics, not only focused on key aspects of their job, but develop new skills rather than doing the same repetitive tasks. We want to thank you so much for watching the program today. Remember you can find all of the content on thecube.net. You can find all of the news from today on siliconangle.com and of course alteryx.com. We also want to thank Alteryx for making this program possible and for sponsoring "theCUBE". For all of my guests, I'm Lisa Martin. We want to thank you for watching and bye for now. (upbeat music)

>>Hey, everyone, welcome back to the programme. Lisa Martin here. I've got two guests joining me. Please welcome back to the Q. Paula Hanson, the chief Revenue officer and president at all tricks. And Jackie Vanderlei Grayling joins us as well. The global head of tax technology at eBay. They're gonna share with you how an all tricks is helping eBay innovate with analytics. Ladies, welcome. It's great to have you both on the programme. >>Thank you, Lisa. Not great to be >>here. >>Yeah, Paula, we're gonna start with you in this programme. We've heard from Jason Klein. We've heard from Allan Jacobsen. They talked about the need to democratise analytics across any organisation to really drive innovation with analytics as they talked about at the forefront of software investments. House all tricks, helping its customers to develop roadmaps for success with analytics. >>Well, thank you, Lisa. Absolutely is about our customers success. And we partner really closely with our customers to develop a holistic approach to their analytics success. And it starts, of course, with our innovative technology and platform. But ultimately we help our customers to create a culture of data literacy and analytics from the top of the organisation starting with the C suite and we partner with our customers to build their road maps for scaling that culture of analytics through things like enablement programmes, skills assessments, hackathons, uh, setting up centres of excellence to help their organisation scale and drive governance of this, uh, analytics capability across the Enterprise. So at the end of the day, it's really about helping our customers to move up their analytics maturity curve with proven technologies and best practises so they can make better business decisions and compete in their respective industries. >>Excellent. Sounds like a very strategic programme. We're gonna unpack that, Jackie, let's bring you into the conversation. Speaking of analytics maturity, one of the things that we talked about in this event is the I. D. C report that showed that 93% of organisations are not utilising the analytic skills of their employees. But then there's eBay. How Jackie did eBay become one of the 7% of organisations who's really maturing and how are you using analytics across the organisation at bay? >>So I think the main thing for us is when we started out was is that you know our especially in finance. They became spreadsheet professionals instead of the things that we really want our influence to add value to. And we realised we have to address that. And we also knew we couldn't wait for all our data to be centralised until we actually start using the data or start automating and be more effective. Um, so ultimately, we really started very, very actively embedding analytics in our people and our data and our processes. >>Starting with people is really critical jacket continuing with you. What was in the roadblocks to analytics adoption that you faced and how did you overcome them? >>So I think you know, Eva is a very data driven company. We have a lot of data. I think we are 27 years around this year. So we have the data, but it is everywhere. And how do you use that data? How do you use it efficiently? How do you get to the data? And I believe that that is definitely one of our biggest roadblocks when we started out and just finding those data sources and finding ways to connect to them, um, to move forward. The other thing is that you know, people were experiencing a lot of frustration. I mentioned before about the spreadsheet professionals, right? And there was no we're not independent. You couldn't move forward. You're dependent on somebody else's roadmap to get to data to get the information you want it. So really finding something that everybody could access analytics or access data. And finally we have to realise, is that this is uncharted territory. This is not exactly something that everybody is used to working with every day. So how do you find something that is easy and that is not so daunting on somebody who's brand new to the field? And I would I would call those out as your as your major roadblocks, because you always have always. But most of the times you have support from the top. In our case we have. But in the end of the day, it's it's our people that need to actually really embrace it and making that accessible for them. I would say it's not to say a road block a block you want to be able to do. >>It's really all about putting people first question for both of you and Paula will start with you and then Jackie will go to you. I think the message in this programme that the audience is watching with us is very clear. Analytics is for everyone should be for everyone. Let's talk now about how both of your organisations are empowering people, those in the organisation that may not have technical expertise to be able to leverage data so that they can actually be data driven colour. >>Yes, well, we leverage our platform across all of our business functions here at all tricks. And just like Jackie explained that eBay finance is probably one of the best examples of how we leverage our own platform to improve our business performance. So just like Jackie mentioned, we have this huge amount of data, uh, flowing through our enterprise, and the opportunity to leverage that into insights and analytics is really endless. So our CFO, Kevin Ruben has been a key sponsor for using our own technology. We use all tricks for forecasting all of our key performance metrics for business planning across our audit function, uh, to help with compliance and regulatory requirements, tax and even to close our books at the end of each quarter. So it's really remain across our business. And at the end of the day, it comes to How do you train users? How do you engage users to lean into this analytic opportunity to discover use cases? And so one of the other things that we've seen many companies do is to gamify that process, to build a game that brings users into the experience for training and to work with each other to problem solve and, along the way, maybe earn badges, depending on the capabilities and trainings that they take and just have a little healthy competition, Uh, as an employee based around who can become more sophisticated in their analytic capability. So I think there's a lot of different ways to do it. And as Jackie mentioned, it's really about ensuring that people feel comfortable that they feel supportive, that they have access to the training that they need, and ultimately that they are given both the skills and the confidence to be able to be a part of this great opportunity of analytics. >>That confidence is key. Jackie talk about some of the ways that you're empowering folks without that technical expertise to really be data driven. >>I think it means to what Paula has said in terms of, you know, getting people excited about it. But it's also understanding that this is a journey and everybody is the different place in their journey. You have folks that's already really advanced. Who's done this every day. And then you have really some folks that this is brand new and, um, or maybe somewhere in between. And it's about how you could get everybody in their different phases to get to the the initial destination. And I say initial because I believe the journey is never really complete. Um, what we have done is that we decided to invest in a group of concept when we got our CFO to sponsor a hackathon. Um, we open it up to everybody in finance, um, in the middle of the pandemic. So everybody was on Zoom, um, and we had and we told people, Listen, we're gonna teach you this tool. It's super easy, and let's just see what you can do. We ended up having 70 injuries. We had only three weeks. So these are people that that do not have a background. They are not engineers and not data scientists and we ended up with 25,000 our savings at the end of the hackathon. Um, from the 70 countries with people that I've never, ever done anything like this before. And there you have the results. And they just went from there because people had a proof of concept. They knew that it worked and they overcame the initial barrier of change. Um, and that's what we are seeing things really, really picking up now >>that's fantastic. And the business outcome that you mentioned that the business impact is massive, helping folks get that confidence to be able to overcome. Sometimes the cultural barriers is key there. I think another thing that this programme has really highlighted is there is a clear demand for data literacy in the job market, regardless of organisation. Can each of you share more about how your empowering the next generation of data workers Paula will start with you? >>Absolutely. And Jackie says it so well, which is that it really is a journey that organisations are on and we, as people in society, are on in terms of up skilling our capabilities. Uh, so one of the things that we're doing here at all tricks to help address the skill set gap on a global level is through a programme that we call Sparked, which is essentially a no cost analyst education programme that we take to universities and colleges globally to help build the next generation of data workers. When we talk to our customers like eBay and many others, they say that it's difficult to find the skills that they want when they're hiring people into the job market. And so this programme is really developed just to do just that, to close that gap and to work hand in hand with students and educators to improve data literacy for the next generation. So we're just getting started with sparked we started last May, but we currently have over 850 educational institutions globally engaged across 47 countries, and we're going to continue to invest here because there's so much opportunity for people, for society and for enterprises when we close gap and empower more people with the necessary analytic skills to solve all the problems that data can help solve. >>So >>I just made a really big impact in such a short time period is gonna be fun to watch the progress of that. Jackie, let's go over to you now Talk about some of the things that eBay is doing to empower the next generation of data workers. >>So we definitely wanted to make sure that we kept implemented from the hackathon that we don't lose that excitement life. So we just launched a programme for evil masterminds and what it basically is. It's an inclusive innovation initiative where we firmly believe that innovation is all upscaling for all analytics role. So it doesn't matter. Your background doesn't matter which function you are in. Come and participate in this where we really focus on innovation, introducing these technologies and upscaling of people. Um, we are apart from that. We also said, Well, we should just keep it to inside the way we have to share this innovation with the community. So we are actually working on developing an analytics high school programme which we hope to pilot by the end of this year. We will actually have high schoolers come in and teach them data essentials, the soft skills around analytics, But also, um, how to use all tricks and we're working with Actually, we're working with spark and they're helping us develop that programme. And we really hope that it is said by the end of the year, have a pilot and then also makes you must have been rolled out in multiple locations in multiple countries and really, really, uh, focused on that whole concept of analytic school >>analytics. Girl sounds like ultra and everybody have a great synergistic relationship there that is jointly aimed at especially kind of going down the stock and getting people when they're younger, interested and understanding how they can be empowered with data across any industry. Paula, let's go back to you. You were recently on the cubes Super Cloud event just a couple of weeks ago and you talked about the challenges the companies are facing as they are navigating what is by default, a multi cloud world. How does the all tricks analytics cloud platform enable CEO s to democratise analytics across their organisation? >>Yes, business leaders and CEO s across all industries are realising that there just aren't enough data scientists in the world to be able to make sense of the massive amounts of data that are flowing through organisations. Last I checked, there was two million data scientists in the world. So that's, uh, woefully underrepresented in terms of the opportunity for people to be a part of the analytics solution. So what we're seeing now with CEO s with business leaders is that they are integrating data analysis and the skill set of data analysis into virtually every job function. Uh, and that is what we think of when we think of analytics for all. And so our mission with all tricks analytics cloud is to empower all of those people in every job function, regardless of their skill set, as Jackie pointed out, from people that would are just getting started all the way to the most sophisticated of technical users. Um, every worker across that spectrum can have a meaningful role in the opportunity to unlock the potential of the data for their company and their organisations. So that's our goal with all tricks, analytics cloud and it operates in a multi cloud world and really helps across all sizes of data sets to blend, cleanse, shape, analyse and report out so that we can break down data silos across the Enterprise and Dr Real Business Outcomes. As a result, of unlocking the potential of data >>as well as really listening that skills gap. As you were saying, There's only two million data scientists. You don't need to be a data scientist. That's the beauty of what all tricks is enabling. And eBay is a great example of that. Jackie, let's go ahead and wrap things with you. You talked a great deal about the analytics maturity that you have fostered at eBay. It obviously has the right culture to adapt to that. Can you talk a little bit and take us out here in terms of where all tricks fits in as that analytics maturity journey continues. And what are some of the things that you're most excited about as analytics truly gets democratised across eBay >>when we start about getting excited about things when it comes to analytics, I can go on all day, but I'll keep it short and sweet for you. Um, I do think we're on the topic full of data scientists, and I really feel that that is your next step for us, anyway. Is that how do we get folks to not see data scientist as this big thing like a rocket scientist it's something completely different and it's something that is in everybody in a certain extent. So, um, game partnering with all tricks to just release uh, ai ml um, solution allowing. You know, folks do not have a data scientist programme but actually build models and be able to solve problems that way. So we have engaged with all turrets and we purchase the licence is quite a few. And right now, through our masterminds programme, we're actually running a four months programme. Um, for all skill levels, um, teaching them ai ml and machine learning and how they can build their own models. Um, we are really excited about that. We have over 50 participants without the background from all over the organisation. We have members from our customer services. We have even some of our engineers are actually participating in the programme will just kick it off. And I really believe that that is our next step. Um, I want to give you a quick example of the beauty of this is where we actually, um, just allow people to go out and think about ideas and come up with things and one of the people in our team who doesn't have a data scientist background at all, was able to develop a solution. Where, um, you know there is a checkout feedback checkout functionality on the eBay side, There's sellers or buyers can pervade them at information. And she built a model to be able to determine what relates to tax specific what is the type of problem and even predict how that problem can be solved before we as human, even stepped in. And now, instead of us or somebody going to debate and try to figure out what's going on there, we can focus on fixing their versus, um, actually just reading through things and not adding any value and its a beautiful tool. And I'm very impressed when we saw the demo and they've been developing that further. >>That sounds fantastic. And I think just the one word that keeps coming to mind. And we've said this a number of times in the programme. Today's empowerment, what you're actually really doing to truly empower people across the organisation with with varying degrees of skill level, going down to the high school level really exciting. We'll have so stay tuned to see what some of the great things are that come from this continued partnership? Ladies, I wanna thank you so much for joining me on the programme today and talking about how all tricks and eBay are really partnering together to democratise analytics and to facilitate its maturity. It's been great talking to you. >>Thank you. >>Thank you so much.

(cheerful music) >> Hello everyone, welcome to today's session of theCUBE's presentation of AWS Startup Showcase, New Breakthroughs in DevOps, Data Analytics, Cloud Management Tools, featuring Okera from the cloud management migration track. I'm John Furrier, your host. We've got two great special guests today, Nong Li, founder and CTO of Okera, and Sanjeev Mohan, principal @SanjMo, and former research vice president of big data and advanced analytics at Gartner. He's a legend, been around the industry for a long time, seen the big data trends from the past, present, and knows the future. Got a great lineup here. Gentlemen, thank you for this, so, life in the trenches, lessons learned across compliance, cloud migration, analytics, and use cases for Fortune 1000s. Thanks for joining us. >> Thanks for having us. >> So Sanjeev, great to see you, I know you've seen this movie, I was saying that in the open, you've at Gartner seen all the visionaries, the leaders, you know everything about this space. It's changing extremely fast, and one of the big topics right out of the gate is not just innovation, we'll get to that, that's the fun part, but it's the regulatory compliance and audit piece of it. It's keeping people up at night, and frankly if not done right, slows things down. This is a big part of the showcase here, is to solve these problems. Share us your thoughts, what's your take on this wide-ranging issue? >> So, thank you, John, for bringing this up, and I'm so happy you mentioned the fact that, there's this notion that it can slow things down. Well I have to say that the old way of doing governance slowed things down, because it was very much about control and command. But the new approach to data governance is actually in my opinion, it's liberating data. If you want to democratize or monetize, whatever you want to call it, you cannot do it 'til you know you can trust said data and it's governed in some ways, so data governance has actually become very interesting, and today if you want to talk about three different areas within compliance regulatory, for example, we all know about the EU GDPR, we know California has CCPA, and in fact California is now getting even a more stringent version called CPRA in a couple of years, which is more aligned to GDPR. That is a first area we know we need to comply to that, we don't have any way out. But then, there are other areas, there is insider trading, there is how you secure the data that comes from third parties, you know, vendors, partners, suppliers, so Nong, I'd love to hand it over to you, and see if you can maybe throw some light into how our customers are handling these use cases. >> Yeah, absolutely, and I love what you said about balancing agility and liberating, in the face of what may be seen as things that slow you down. So we work with customers across verticals with old and new regulations, so you know, you brought up GDPR. One of our clients is using this to great effect to power their ecosystem. They are a very large retail company that has operations and customers across the world, obviously the importance of GDPR, and the regulations that imposes on them are very top of mind, and at the same time, being able to do effective targeting analytics on customer information is equally critical, right? So they're exactly at that spot where they need this customer insight for powering their business, and then the regulatory concerns are extremely prevalent for them. So in the context of GDPR, you'll hear about things like consent management and right to be forgotten, right? I, as a customer of that retailer should say "I don't want my information used for this purpose," right? "Use it for this, but not this." And you can imagine at a very, very large scale, when you have a billion customers, managing that, all the data you've collected over time through all of your devices, all of your telemetry, really, really challenging. And they're leveraging Okera embedded into their analytics platform so they can do both, right? Their data scientists and analysts who need to do everything they're doing to power the business, not have to think about these kind of very granular customer filtering requirements that need to happen, and then they leverage us to do that. So that's kind of new, right, GDPR, relatively new stuff at this point, but we obviously also work with customers that have regulations from a long long time ago, right? So I think you also mentioned insider trading and that supply chain, so we'll talk to customers, and they want really data-driven decisions on their supply chain, everything about their production pipeline, right? They want to understand all of that, and of course that makes sense, whether you're the CFO, if you're going to make business decisions, you need that information readily available, and supply chains as we know get more and more and more complex, we have more and more integrated into manufacturing and other verticals. So that's your, you're a little bit stuck, right? You want to be data-driven on those supply chain analytics, but at the same time, knowing the details of all the supply chain across all of your dependencies exposes your internal team to very high blackout periods or insider trading concerns, right? For example, if you knew Apple was buying a bunch of something, that's maybe information that only a select few people can have, and the way that manifests into data policies, 'cause you need the ability to have very, very scalable, per employee kind of scalable data restriction policies, so they can do their job easier, right? If we talk about speeding things up, instead of a very complex process for them to get approved, and approved on SEC regulations, all that kind of stuff, you can now go give them access to the part of the supply chain that they need, and no more, and limit their exposure and the company's exposure and all of that kind of stuff. So one of our customers able to do this, getting two orders of magnitude, a 100x reduction in the policies to manage the system like that. >> When I hear you talking like that, I think the old days of "Oh yeah, regulatory, it kind of slows down innovation, got to go faster," pretty basic variables, not a lot of combination of things to check. Now with cloud, there seems to be combinations, Sanjeev, because how complicated has the regulatory compliance and audit environment gotten in the past few years, because I hear security in a supply chain, I hear insider threats, I mean these are security channels, not just compliance department G&A kind of functions. You're talking about large-scale, potentially combinations of access, distribution, I mean it seems complicated. How much more complicated is it now, just than it was a few years ago? >> So, you know the way I look at it is, I'm just mentioning these companies just as an example, when PayPal or Ebay, all these companies started, they started in California. Anybody who ever did business on Ebay or PayPal, guess where that data was? In the US in some data center. Today you cannot do it. Today, data residency laws are really tough, and so now these organizations have to really understand what data needs to remain where. On top of that, we now have so many regulations. You know, earlier on if you were healthcare, you needed to be HIPAA compliant, or banking PCI DSS, but today, in the cloud, you really need to know, what data I have, what sensitive data I have, how do I discover it? So that data discovery becomes really important. What roles I have, so for example, let's say I work for a bank in the US, and I decide to move to Germany. Now, the old school is that a new rule will be created for me, because of German... >> John: New email address, all these new things happen, right? >> Right, exactly. So you end up with this really, a mass of rules and... And these are all static. >> Rules and tools, oh my god. >> Yeah. So Okera actually makes a lot of this dynamic, which reduces your cloud migration overhead, and Nong used some great examples, in fact, sorry if I take just a second, without mentioning any names, there's one of the largest banks in the world is going global in the digital space for the first time, and they're taking Okera with them. So... >> But what's the point? This is my next topic in cloud migration, I want to bring this up because, complexity, when you're in that old school kind of data center, waterfall, these old rules and tools, you have to roll this out, and it's a pain in the butt for everybody, it's a hassle, huge hassle. Cloud gives the agility, we know that, and cloud's becoming more secure, and I think now people see the on-premise, certainly things that'd be on-premises for secure things, I get that, but when you start getting into agility, and you now have cloud regions, you can start being more programmatic, so I want to get you guys' thoughts on the cloud migration, how companies who are now lifting and shifting, replatforming, what's the refactoring beyond that, because you can replatform in the cloud, and still some are kind of holding back on that. Then when you're in the cloud, the ones that are winning, the companies that are winning are the ones that are refactoring in the cloud. Doing things different with new services. Sanjeev, you start. >> Yeah, so you know, in fact lot of people tell me, "You know, we are just going to lift and shift into the cloud." But you're literally using cloud as a data center. You still have all the, if I may say, junk you had on-prem, you just moved it into the cloud, and now you're paying for it. In cloud, nothing is free. Every storage, every processing, you're going to pay for it. The most successful companies are the ones that are replatforming, they are taking advantage of the platform as a service or software as a service, so that includes things like, you pay as you go, you pay for exactly the amount you use, so you scale up and scale down or scale out and scale in, pretty quickly, you know? So you're handling that demand, so without replatforming, you are not really utilizing your- >> John: It's just hosting. >> Yeah, you're just hosting. >> It's basically hosting if you're not doing anything right there. >> Right. The reason why people sometimes resist to replatform, is because there's a hidden cost that we don't really talk about, PaaS adds 3x to IaaS cost. So, some organizations that are very mature, and they have a few thousand people in the IT department, for them, they're like "No, we just want to run it in the cloud, we have the expertise, and it's cheaper for us." But in the long run, to get the most benefit, people should think of using cloud as a service. >> Nong what's your take, because you see examples of companies, I'll just call one out, Snowflake for instance, they're essentially a data warehouse in the cloud, they refactored and they replatformed, they have a competitive advantage with the scale, so they have things that others don't have, that just hosting. Or even on-premise. The new model developing where there's real advantages, and how should companies think about this when they have to manage these data lakes, and they have to manage all these new access methods, but they want to maintain that operational stability and control and growth? >> Yeah, so. No? Yeah. >> There's a few topics that are all (indistinct) this topic. (indistinct) enterprises moving to the cloud, they do this maybe for some cost savings, but a ton of it is agility, right? The motor that the business can run at is just so much faster. So we'll work with companies in the context of cloud migration for data, where they might have a data warehouse they've been using for 20 years, and building policies over that time, right? And it's taking a long time to go proof of access and those kind of things, made more sense, right? If it took you months to procure a physical infrastructure, get machines shipped to your data center, then this data access taking so long feels okay, right? That's kind of the same rate that everything is moving. In the cloud, you can spin up new infrastructure instantly, so you don't want approvals for getting policies, creating rules, all that stuff that Sanjeev was talking about, that being slow is a huge, huge problem. So this is a very common environment that we see where they're trying to do that kind of thing. And then, for replatforming, again, they've been building these roles and processes and policies for 20 years. What they don't want to do is take 20 years to go migrate all that stuff into the cloud, right? That's probably an experience nobody wants to repeat, and frankly for many of them, people who did it originally may or may not be involved in this kind of effort. So we work with a lot of companies like that, they have their, they want stability, they got to have the business running as normal, they got to get moving into the new infrastructure, doing it in a new way that, you know, with all the kind of lessons learned, so, as Sanjeev said, one of these big banks that we work with, that classical story of on-premise data warehousing, maybe a little bit of Hadoop, moved onto AWS, S3, Snowflake, that kind of setup, extremely intricate policies, but let's go reimagine how we can do this faster, right? What we like to talk about is, you're an organization, you need a design that, if you onboarded 1000 more data users, that's got to be way, way easier than the first 10 you onboarded, right? You got to get it to be easier over time, in a really, really significant way. >> Talk about the data authorization safety factor, because I can almost imagine all the intricacies of these different tools creates specialism amongst people who operate them. And each one might have their own little authorization nuance. Trend is not to have that siloed mentality. What's your take on clients that want to just "Hey, you know what? I want to have the maximum agility, but I don't want to get caught in the weeds on some of these tripwires around access and authorization." >> Yeah, absolutely, I think it's real important to get the balance of it, right? Because if you are an enterprise, or if you have diversive teams, you want them to have the ability to use tools as best of breed for their purpose, right? But you don't want to have it be so that every tool has its own access and provisioning and whatever, that's definitely going to be a security, or at least, a lot of friction for you to get things going. So we think about that really hard, I think we've seen great success with things like SSO and Okta, right? Unifying authentication. We think there's a very, very similar thing about to happen with authorization. You want that single control plane that can integrate with all the tools, and still get the best of what you need, but it's much, much easier (indistinct). >> Okta's a great example, if people don't want to build their own thing and just go with that, same with what you guys are doing. That seems to be the dots that are connecting you, Sanjeev. The ease of use, but yet the stability factor. >> Right. Yeah, because John, today I may want to bring up a SQL editor to go into Snowflake, just as an example. Tomorrow, I may want to use the Azure Bot, you know? I may not even want to go to Snowflake, I may want to go to an underlying piece of data, or I may use Power BI, you know, for some reason, and come from Azure side, so the point is that, unless we are able to control, in some sort of a centralized manner, we will not get that consistency. And security you know is all or nothing. You cannot say "Well, I secured my Snowflake, but if you come through HTFS, Hadoop, or some, you know, that is outside of my realm, or my scope," what's the point? So that is why it is really important to have a watertight way, in fact I'm using just a few examples, maybe tomorrow I decide to use a data catalog, or I use Denodo as my data virtualization and I run a query. I'm the same identity, but I'm using different tools. I may use it from home, over VPN, or I may use it from the office, so you want this kind of flexibility, all encompassed in a policy, rather than a separate rule if you do this and this, if you do that, because then you end up with literally thousands of rules. >> And it's never going to stop, either, it's like fashion, the next tool's going to come out, it's going to be cool, and people are going to want to use it, again, you don't want to have to then move the train from the compliance side this way or that way, it's a lot of hassle, right? So we have that one capability, you can bring on new things pretty quickly. Nong, am I getting it right, this is kind of like the trend, that you're going to see more and more tools and/or things that are relevant or, certain use cases that might justify it, but yet, AppSec review, compliance review, I mean, good luck with that, right? >> Yeah, absolutely, I mean we certainly expect tools to continue to get more and more diverse, and better, right? Most innovation in the data space, and I think we... This is a great time for that, a lot of things that need to happen, and so on and so forth. So I think one of the early goals of the company, when we were just brainstorming, is we don't want data teams to not be able to use the tools because it doesn't have the right security (indistinct), right? Often those tools may not be focused on that particular area. They're great at what they do, but we want to make sure they're enabled, they do some enterprise investments, they see broader adoption much easier. A lot of those things. >> And I can hear the sirens in the background, that's someone who's not using your platform, they need some help there. But that's the case, I mean if you don't get this right, there are some consequences, and I think one of the things I would like to bring up on next track is, to talk through with you guys is, the persona pigeonhole role, "Oh yeah, a data person, the developer, the DevOps, the SRE," you start to see now, developers and with cloud developers, and data folks, people, however they get pigeonholed, kind of blending in, okay? You got data services, you got analytics, you got data scientists, you got more democratization, all these things are being kicked around, but the notion of a developer now is a data developer, because cloud is about DevOps, data is now a big part of it, it's not just some department, it's actually blending in. Just a cultural shift, can you guys share your thoughts on this trend of data people versus developers now becoming kind of one, do you guys see this happening, and if so, how? >> So when, John, I started my career, I was a DBA, and then a data architect. Today, I think you cannot have a DBA who's not a developer. That's just my opinion. Because there is so much of CICD, DevOps, that happens today, and you know, you write your code in Python, you put it in version control, you deploy using Jenkins, you roll back if there's a problem. And then, you are interacting, you're building your data to be consumed as a service. People in the past, you would have a thick client that would connect to the database over TCP/IP. Today, people don't want to connect over TCP/IP necessarily, they want to go by HTTP. And they want an API gateway in the middle. So, if you're a data architect or DBA, now you have to worry about, "I have a REST API call that's coming in, how am I going to secure that, and make sure that people are allowed to see that?" And that was just yesterday. >> Exactly. Got to build an abstraction layer. You got to build an abstraction layer. The old days, you have to worry about schema, and do all that, it was hard work back then, but now, it's much different. You got serverless, functions are going to show way... It's happening. >> Correct, GraphQL, and semantic layer, that just blows me away because, it used to be, it was all in database, then we took it out of database and we put it in a BI tool. So we said, like BusinessObjects started this whole trend. So we're like "Let's put the semantic layer there," well okay, great, but that was when everything was surrounding BusinessObjects and Oracle Database, or some other database, but today what if somebody brings Power BI or Tableau or Qlik, you know? Now you don't have a semantic layer access. So you cannot have it in the BI layer, so you move it down to its own layer. So now you've got a semantic layer, then where do you store your metrics? Same story repeats, you have a metrics layer, then the data centers want to do feature engineering, where do you store your features? You have a feature store. And before you know, this stack has disaggregated over and over and over, and then you've got layers and layers of specialization that are happening, there's query accelerators like Dremio or Trino, so you've got your data here, which Nong is trying really hard to protect, and then you've got layers and layers and layers of abstraction, and networks are fast, so the end user gets great service, but it's a nightmare for architects to bring all these things together. >> How do you tame the complexity? What's the bottom line? >> Nong? >> Yeah, so, I think... So there's a few things you need to do, right? So, we need to re-think how we express security permanence, right? I think you guys have just maybe in passing (indistinct) talked about creating all these rules and all that kind of stuff, that's been the way we've done things forever. We get to think about policies and mechanisms that are much more dynamic, right? You need to really think about not having to do any additional work, for the new things you add to the system. That's really, really core to solving the complexity problem, right? 'Cause that gets you those orders of magnitude reduction, system's got to be more expressive and map to those policies. That's one. And then second, it's got to be implemented at the right layer, right, to Sanjeev's point, close to the data, and it can service all of those applications and use cases at the same time, and have that uniformity and breadth of support. So those two things have to happen. >> Love this universal data authorization vision that you guys have. Super impressive, we had a CUBE Conversation earlier with Nick Halsey, who's a veteran in the industry, and he likes it. That's a good sign, 'cause he's seen a lot of stuff, too, Sanjeev, like yourself. This is a new thing, you're seeing compliance being addressed, and with programmatic, I'm imagining there's going to be bots someday, very quickly with AI that's going to scale that up, so they kind of don't get in the innovation way, they can still get what they need, and enable innovation. You've got cloud migration, which is only going faster and faster. Nong, you mentioned speed, that's what CloudOps is all about, developers want speed, not things in days or hours, they want it in minutes and seconds. And then finally, ultimately, how's it scale up, how does it scale up for the people operating and/or programming? These are three major pieces. What happens next? Where do we go from here, what's, the customer's sitting there saying "I need help, I need trust, I need scale, I need security." >> So, I just wrote a blog, if I may diverge a bit, on data observability. And you know, so there are a lot of these little topics that are critical, DataOps is one of them, so to me data observability is really having a transparent view of, what is the state of your data in the pipeline, anywhere in the pipeline? So you know, when we talk to these large banks, these banks have like 1000, over 1000 data pipelines working every night, because they've got that hundred, 200 data sources from which they're bringing data in. Then they're doing all kinds of data integration, they have, you know, we talked about Python or Informatica, or whatever data integration, data transformation product you're using, so you're combining this data, writing it into an analytical data store, something's going to break. So, to me, data observability becomes a very critical thing, because it shows me something broke, walk me down the pipeline, so I know where it broke. Maybe the data drifted. And I know Okera does a lot of work in data drift, you know? So this is... Nong, jump in any time, because I know we have use cases for that. >> Nong, before you get in there, I just want to highlight a quick point. I think you're onto something there, Sanjeev, because we've been reporting, and we believe, that data workflows is intellectual property. And has to be protected. Nong, go ahead, your thoughts, go ahead. >> Yeah, I mean, the observability thing is critically important. I would say when you want to think about what's next, I think it's really effectively bridging tools and processes and systems and teams that are focused on data production, with the data analysts, data scientists, that are focused on data consumption, right? I think bridging those two, which cover a lot of the topics we talked about, that's kind of where security almost meets, that's kind of where you got to draw it. I think for observability and pipelines and data movement, understanding that is essential. And I think broadly, on all of these topics, where all of us can be better, is if we're able to close the loop, get the feedback loop of success. So data drift is an example of the loop rarely being closed. It drifts upstream, and downstream users can take forever to figure out what's going on. And we'll have similar examples related to buy-ins, or data quality, all those kind of things, so I think that's really a problem that a lot of us should think about. How do we make sure that loop is closed as quickly as possible? >> Great insight. Quick aside, as the founder CTO, how's life going for you, you feel good? I mean, you started a company, doing great, it's not drifting, it's right in the stream, mainstream, right in the wheelhouse of where the trends are, you guys have a really crosshairs on the real issues, how you feeling, tell us a little bit about how you see the vision. >> Yeah, I obviously feel really good, I mean we started the company a little over five years ago, there are kind of a few things that we bet would happen, and I think those things were out of our control, I don't think we would've predicted GDPR security and those kind of things being as prominent as they are. Those things have really matured, probably as best as we could've hoped, so that feels awesome. Yeah, (indistinct) really expanded in these years, and it feels good. Feels like we're in the right spot. >> Yeah, it's great, data's competitive advantage, and certainly has a lot of issues. It could be a blocker if not done properly, and you're doing great work. Congratulations on your company. Sanjeev, thanks for kind of being my cohost in this segment, great to have you on, been following your work, and you continue to unpack it at your new place that you started. SanjMo, good to see your Twitter handle taking on the name of your new firm, congratulations. Thanks for coming on. >> Thank you so much, such a pleasure. >> Appreciate it. Okay, I'm John Furrier with theCUBE, you're watching today's session presentation of AWS Startup Showcase, featuring Okera, a hot startup, check 'em out, great solution, with a really great concept. Thanks for watching. (calm music)

(upbeat music) >> Welcome back to HPE Discover 2021, the virtual version. My name is Dave Vellante, and you're watching theCUBE. As the saying goes, follow the money. And with me to talk about HPE Financial Services and the value that it can bring to customers are two great guests, Brad, Shapiro's VP and managing director of the Enterprise Business at HPE Financial Services. And Paul Sheeran is Managing Director of Worldwide Channel and SMB for HPE Financial Services. Gents, welcome to theCUBE. Come on in. >> Thanks Dave, we really appreciate you having us. >> Hi, Dave. >> So Brad, why don't you start us off? Give us the rundown on HPE Financial Services. What's the scope of your services? Should we think of you as a bank? And maybe you could talk about some of the things that you do beyond financing. >> Yeah, that sounds great. So look, we are so much more than banking. Our mission is to create investment capacity to help customers accelerate their transformation. And maybe you could think of us as kind of like a two-in-one partner. We're part-CIO, part-CFO. We kind of refer to ourselves as the CIFO, if you will. And we've got an expertise in a number of different areas. Of course, we'll start with financial. And yes, we offer financial services, and we do an awful lot of financial solutioning. In our portfolio, it's over 13 billion of assets that have been financed. So that is a core competency for us. But we're more than that. We focus also on the technology side of things. And we have expertise in asset management. And we deal with multiple generations of technologies and all major manufacturers as well, not just HPE, but we understand technology and all different types, all different ages of technology. And lastly, we play a pretty big role around sustainability. HPE takes a leadership position when it comes to sustainability. And a lot of our capabilities around the circular economy and putting assets back into reuse play an important role in not only helping customers financially, but helping them meet their sustainability goals. >> I want to come back and ask you more about that, but Paul, I wonder... First of all, I like the CIFO. That's a great, little nomenclature. But Paul, if you're a small business, the CEO is also sometimes the CIO, is sometimes the CFO, a lot of hats. So maybe you could talk about the role that you guys play for SMBs and also channel partners. Channel's a whole different ball game. They want to make margin, they want to grow their business. So maybe you could discuss some of the differences in that channel. >> Yeah. Sure, Dave. Well, starting with the SMB customer is really critical part of our portfolio. As you said, they cover all the roles, so the CIO, CFO. And their budgets can be tight. And especially given the last 18 months, if you read some of the data out there, the budgets are really constrained, especially for the SMB customer. So we try and do, and what our mission is, is what we call creating investment capacity, giving budgets a boost, bringing that vitality to the SMB customer base, to all our customers, but especially SMB customers to help them be able to invest in their digital transformations going forward. So crucial now that all our customers are able to continue to invest in technology. And the pandemic clearly brought it home how important having a digital capability it is. So SMB budgets are tight, and what we try and do is give them that boost, give them that vitality to actually continue to advance ahead and make the right investments for the future. And then from the partners, we actually do a four and a half thousand partners around the world. As you said, partners, they're also not only looking for financial solutions, but how do we differentiate ourselves is to try and help that partner move to a digital platform. We have invested heavily in our digital tools over the last couple of years. So in terms of offering solutions, it can be literally zero touch, low touch so the partner community can plug into our platforms. We also help them on that journey as a service. So technology is moving to as a service. People want to consume technology as a service like they do in the rest of their lives. It's all about subscription. And partners need help to be able to move to another service way. Hopefully GreenLake is the answer. So we support HPE GreenLake's offering. But there's different parts along the way for partners that we look to help them. And last but not least is helping them about asset management. As Brad said, it's all about the assets and understanding how those assets are managed. And helping the partners, having a relevant conversation with their customers as to how best to put in an asset management strategy for their customers. So three areas that we look to differentiate ourselves, Dave. >> We got a lot to talk about. So I want to come back and talk about as a service as well. But Brad, I want to go back to sustainability. So is it just the right thing to do? What's the financial case? Is it good business as well, and where do you fit? >> Yeah, so we believe that sustainability is good for the environment, obviously, but it's also good for business. And when you think about what we bring to the table and those assets back into reuse. So we handle between three and four million assets a year, and over 90% of those, we put back into reuse, with about 10% going into recycling. Putting those back into reuse, the customer that has those assets, we can monetize those assets and help accelerate transformation. So we monetize the asset, and we fund that transition in that transformation so we can really help customers get more budget than they were expecting by leveraging what they would deem to be end-of-life assets, but we find another home for those assets. So it definitely helps customers accelerate the transformation, while being good for the world, good for the environment. >> And that's true, Paul, for SMBs, just maybe on a smaller scale, and definitely makes sense for the channel, right? >> Absolutely. Absolutely. Sustainability now is key. Certainly key for our channel partners is moving from a nice-to-have to a must-have. So absolutely, totally agree. >> Yeah. And it's almost like gain sharing. I mean, sometimes we sell used equipment on eBay. It helps fund future business or future transformation. So let's get into the transformations. Everybody talks about digital transformation. Coming into the pandemic, everybody talked about it, but there was a lot of complacency. We've all seen the wrecking ball and the acceleration we talk about all the time, but what role does HPE Financial Services, and do you have any specific solutions that support digital transformations? Any examples there? Maybe Brad, you could start it off. >> Yeah. Yeah. So I'll start off, and then Paul, feel free to jump in. Look Dave, what I would say is the pandemic taught us that every company is a technology company. And where HPFS comes in is we're looking to provide the investment capacity, which is the lifeblood of a company's digital roadmap. So if you don't have the investment capacity, there is no transformation. So when something like the pandemic comes up, and you can't budget for a pandemic, and revenues are down and budgets are getting squeezed, you really need a partner to help you with that. How do you uncover that investment capacity? So we we've talked to lots of customers. We've also done some research, and the ESG group and analysts basically found that 73% of organizations, not surprisingly, either delayed or canceled projects around IT transformation because of all the uncertainty. So what we're looking to do is leverage all of our capabilities in a timely fashion. Last year, we announced the idea of payment holidays and deferred payments so you could keep your transformation going and not have to pay for it for a full year. And now we look at it as we're coming out of the pandemic. And what we're looking to help customers with is one, help them transition their existing infrastructure into a modernized consumption model like GreenLake. Also looking to accelerate the velocity of the transformation programs by leveraging our capabilities around asset upcycling, as well as our accelerated migration program. And last, looking at our existing customers really doing some financial engineering with them, so they can stretch their budgets more and expand the budget to be able to handle new projects. >> Yeah, I mean, Paul, I think Brad nailed it. You're right, their transformations are strategic. They had to fund VDI initiatives or endpoint security or find some cash to buy laptops to support people at home. People were pulling out their servers and sticking them in their trunk and driving to their home because they couldn't get laptops for awhile. And so what are you seeing now, Paul, particularly in the channel. And of course, again, SMBs were squeezed. Maybe they don't have the liquidity that some of these large public companies have. A lot of people just shored up their balance sheets during the pandemic. Maybe the SMB doesn't have as much advantage to do that. But what are you seeing in regard to the sort of bounce back of spend in more strategic areas like transformation? >> Well, I think what we're seeing right now and what we're hearing, especially for SMB customer, is cash is king. It's all about cash preservation. It's about making sure that... You'll hear some studies where some SMB customers only have three or four months left of cash in their kitty to keep their businesses running. So that is really top of mind now. Would they have to invest? If they don't want invest, they're going to be dead in the water to stay ahead of the competition. So what we're looking to do is really help those customers preserve that cash and reach and look for different ways about how to boost their budget. There's actually nothing better than an example. Brad laid out very nicely in terms of what we can do. Bringing it to life, not so much an SMB customer, but there is UNAD. And UNAD is a university in Columbia based in Bogota. And their mission is very simple, it's all about excellence and learning. But as they went into the pandemic, they needed to invest in their distance learning platforms to really help their students. And like most businesses, cash and budget was being squeezed. Revenues were tight. So it would've been very easy to postpone that investment. Well, what we did with UNAD and working with UNAD under IT team was firstly to understand their existing IT estate and really see what assets are being utilized, what are not being utilized, what assets have reached or ended their useful life. And you'd be amazed. And it's not just the data center, we can work right across their whole estate. So as well as the data center, we look at the PCs. To your point, David, we look at even their print estate. And we identified many, many assets that were being underutilized and other assets that were end of life. So we were able to take those assets back and actually release value and boosts UNAD's budget. And some of those assets could not. They had no value. And sustainability was top of their agenda as well. As you'd imagine, the university wanted to lead and show their students that sustainability is key. So we were able to take those assets back and actually recycle them in a very environmentally sound way. So that was the first step to actually inject some cash into their budgets. The next step then was to look at their existing financial contracts that they had in place where maybe some of their banks and actually restructured those contracts to actually give them additional capacity to invest right now in technology. And I'm delighted to say they partnered with the HPE team, I mean, Aruba, to actually continue their five-year roadmap and actually improved their distance learning platforms. So I just thought that was a really good example right now and in the current climate as to show when we work together with our customers, what's actually possible. >> So let's talk a little bit more about GreenLake. I mean, for decades, I mean, even if I go back to the '80s, I saw financial instruments to sort of rent essentially, but it's different. GreenLake, HPE, has pivoted its entire company to as a service. And I want to understand better what role HPE Financial Services plays in making that transition. It's obviously a crucial part of the financing piece, but Brad, maybe you could tell us a little bit more there. >> Yeah, sure. And I think the great thing about GreenLake is it's more than just a consumption model, it's really providing that cloud experience, on-prem, and being able for customers to really manage a hybrid cloud experience. But where HPEFS plays a role, again, it's around our knowledge and ability around assets. So we are underneath GreenLake, doing financial engineering, managing the assets. But the biggest thing, when you think about how does a customer transition? If they're in a traditional cash purchase paradigm, the cost of change and figuring out how to move into a new type of paradigm and new consumption model can be daunting. So HPFS works closely with our GreenLake team and the customer, and we can take those existing assets and look to accelerate the migration into a GreenLake. A great example of that, a public sector customer, Kern County, they were in that cash paradigm, they had lots of assets. Like most entities, they were under pressure from a budget perspective. Tax revenues were down for a couple years in a row. So not only did moving to a GreenLake model provide some cost savings, and cost savings are important, but it also allowed them to deliver the services they needed to their constituents because they had that pay for use type of flexibility. They didn't have a long delay in procuring and provisioning equipment when they needed to roll something out. And again, once again, HPFS was able to monetize their existing assets, roll those into a GreenLake solution and help self-fund that transformation and really accelerate it to get from that cash paradigm model to a new GreenLake consumption model. >> Paul, what about the channel? I mean, on the one hand, I could see the channels loving GreenLake because there's a lot of services involved, and it's sort of an ongoing drip of cash as opposed to the sort of big hit. But on the other hand, it's the ongoing drip of cash as opposed to the big hit. What's the conversations like with the channel? How is that going? I mean, clearly it's the future, but how do they see it? >> I wouldn't say a drip of cash. We would call it an in-use revenue where it's very predictable, which is actually also a good thing, rather than a sort of a one-and-done solution. So clearly, GreenLake is very important to our channel partners, and we're seeing some really good adoption across the world. Again, we underpin that. The other thing to say is a lot of channel partners, as you likely say, want as sell services and become service providers. And what we also do is support not just the data center, but also workplace and print. And what you'll see on the printing side for many, many years, the print partners have been selling a contractual type of model. But a lot of partners now are moving all of their core portfolio into as a service. And there's different parts. It's nearly a cash to as a service journey, and there's different parts of that ladder on the way. And we will look to help our partners get along that ladder and hopefully position GreenLake. But there's also more simpler solutions like subscription that we can position on that journey. So it's really helping that partner get the confidence and the financial wherewithal and the infrastructure to get on the as a service journey. >> How about solutions? I mean, you guys have had some recent announcements. Maybe Brad, you can take us through sort of what the highlights of those were. >> Sure. So yeah, the first announcement was really the example I just provided, which was how do we transition customers to GreenLake? So again, that's a really important step for many customers, and something that we can help them with is moving from that existing paradigm to GreenLake. The second is really helping customers create velocity to move their transformation programs faster. And we do that in a number of ways, but again, all around the asset in our asset management expertise, whether we look to put those assets back into reuse in their facility, or if we look to monetize those assets and put them into reuse with a different customer. Really, it's all around how do we accelerate the customers transformation as we come out of a pandemic. And then lastly, the offering is really focused on how can we help the customer look at existing budget and really financially engineer where they're spending their money to create new pools of budget and cash so they can fund new projects. So it's interesting because when I look at the customers that we're doing these things with, it really spans every industry. So we're dealing with financial services and insurance companies, communications and broadcasting, travel and hospitality, you name it, manufacturing. So the interesting thing is, while sometimes you come out with solutions that are very industry-specific, I think our circumstances today really span lots of industries, both in the commercial and the public sector. And we're finding that these offers are really relevant right now for customers. >> Let's zoom out for a bit. And Brad, let's start with you, and then Paul, I want to get your unique perspectives from the standpoint of SMB in the channel. Summarize your overall strategy in that context. And then I'm interested in, how important do you feel the HPE Financial Services is with regards... And of course, you guys are biased, but that's okay, I want to hear your bias view. How important is it in the grand scheme of actually doing business with HPE. And I'm interested in in why HPE and how much of a competitive advantage you bring relative to some of your major competitors. >> Yeah, sure. So look, the strategy, in my mind, I'll start with HPFS, it's really making sure that we're working closely with our customers, understanding their needs from a business perspective and what business outcomes they're trying to achieve and then marrying both the financial planning and the technology planning to help those customers deliver and achieve those business outcomes. Doing that, also in a way that is sustainable and is good for the environment and helps customers achieve their sustainability initiatives. So kind of marrying that financial technology and sustainability portion of it. From my perspective, I think HPE is a fantastic partner. One, we've been at GreenLake for quite a while, and it continues to evolve. The experiences that we can provide customers now are significantly advanced from when flex capacity came out years and years and years ago. So I really think if a customer took a look at GreenLake a few years ago, you need to keep looking at it because it really has evolved, really creates a unique experience. But I think it's the combination of our technology. We have great technology in our portfolio. We have a fantastic model in GreenLake, and then we have all of the financial engineering expertise around assets and lifecycles and how to get the most out of your IT investment. And we are a partner. If you have sustainability initiatives, I mean, HPE talks the talk, we walk the walk. We do all of this for ourselves, and then we bring those practices out and share best practices with customers. So I really think it's a great time to partner with HP if you're a customer. >> Right, thank you for that, Brad. Paul, what would you add for your constituents? >> Brad, said it beautifully. So just a couple of points I'd add in. From a partner perspective, we are actually in every corner of the world. So we have that global footprint. And then as you see, consolidation in the market, that's very important, not only for our customers, but also for our partners, more and more solutions are going cross border and involve different regions. And we look to make sure that we're globally consistent in how we work with our partners and work with our customers. And the final thing I'd say is we get very excited about supporting our HPE colleagues. But from a channel perspective, we actually also support HPI, HP Inc. You will recall, before separation, that the companies did. So we also support the workplace and print environments, plus third party vendors, which again, is important for the channel community. Why do you need a one-stop shell? And where you'll often have a mixed technology and the solution. So we're there for that as well and always have been. And I think the partner community love our consistency there >> It's a nice arrow when you quiver. And of course we've seen laptop demand explode. And it looks like it's going to sustain for a while here. It's hard to predict, but Paul, still with you, tell us, thinking about the future, what's getting you jazzed up? >> Well, I said we have a global footprint, and every country is in a different place right now. As we sort of come out of the pandemic, some countries are still in the midst of it. But what gets me jazzed up and what gets me excited is the sense of optimism. I think we're sort of figured out how to navigate our way out of this pandemic and the current environment. And customers all recognize the need to invest in technology. Technology is the way forward. So that means having the capacity, investment capacity, the investment vitality, to make that investment. So what gets me excited is what we do is important and we're there to help. >> Great. Thank you. And then Brad, two-part question for you to bring us home. So what are you excited about, and what do you got going at Discover? >> So in terms of my excitement, I think Paul said it well, every company is a technology company. And when we see that everybody is going through a digital transformation, quite frankly, we at HPEFS are going through our own digital transformation. Paul mentioned earlier about Technomics. We have omni-channel ways of engaging with us that are consistent. We're looking at our customer and partner experience and continuing to improve those. So we're not resting on our laurels in what we've done in the past, we continue to change, to modernize, to create new and better ways of doing business with our customer base. So the exciting part, for me, is that change that comes with innovation and technology. And I just think HPE is a great place to be right now with all of that innovation going on. So you asked about Discover. So we're really excited. We've got a spotlight with Irv Rothman focused on investment agility and key to growth and regeneration. So that's really exciting. We have a few breakouts, making technology a force for good, getting back on track that create the investment vitality to take on the world and investment strategies to accelerate innovation in a disruptive world. So really excited about that. And then last, we've got some demos. We have a live interactive demo on our technology renewal center, as well as some on-demand demos of those renewal centers as well. So we've got a lot going on at Discover, and we're really excited about it. >> Great. Gentlemen, thank you for that. So I mean, look, cost of capital is low, but to have a technology partner with you that's also has financial expertise, that, to me, is a killer combination. Guys, thanks so much for coming on theCUBE. I really appreciate your time. >> Dave, thanks for having us. >> Thanks, Dave. >> All right, and thank you for watching theCUBE's continuous coverage of HPE Discover 2021, the virtual edition. Keep it right there for more great content. (upbeat music)

(upbeat music) >> Welcome back to HPE Discover 2021, the virtual version. My name is Dave Vellante, and you're watching theCUBE. As the saying goes, follow the money. And with me to talk about HPE Financial Services and the value that it can bring to customers are two great guests, Brad, Shapiro's VP and managing director of the Enterprise Business at HPE Financial Services. And Paul Sheeran is Managing Director of Worldwide Channel and SMB for HPE Financial Services. Gents, welcome to theCUBE. Come on in. >> Thanks Dave, we really appreciate you having us. >> Hi, Dave. >> So Brad, why don't you start us off? Give us the rundown on HPE Financial Services. What's the scope of your services? Should we think of you as a bank? And maybe you could talk about some of the things that you do beyond financing. >> Yeah, that sounds great. So look, we are so much more than banking. Our mission is to create investment capacity to help customers accelerate their transformation. And maybe you could think of us as kind of like a two-in-one partner. We're part-CIO, part-CFO. We kind of refer to ourselves as the CIFO, if you will. And we've got an expertise in a number of different areas. Of course, we'll start with financial. And yes, we offer financial services, and we do an awful lot of financial solutioning. In our portfolio, it's over 13 billion of assets that have been financed. So that is a core competency for us. But we're more than that. We focus also on the technology side of things. And we have expertise in asset management. And we deal with multiple generations of technologies and all major manufacturers as well, not just HPE, but we understand technology and all different types, all different ages of technology. And lastly, we play a pretty big role around sustainability. HPE takes a leadership position when it comes to sustainability. And a lot of our capabilities around the circular economy and putting assets back into reuse play an important role in not only helping customers financially, but helping them meet their sustainability goals. >> I want to come back and ask you more about that, but Paul, I wonder... First of all, I like the CIFO. That's a great, little nomenclature. But Paul, if you're a small business, the CEO is also sometimes the CIO, is sometimes the CFO, a lot of hats. So maybe you could talk about the role that you guys play for SMBs and also channel partners. Channel's a whole different ball game. They want to make margin, they want to grow their business. So maybe you could discuss some of the differences in that channel. >> Yeah. Sure, Dave. Well, starting with the SMB customer is really critical part of our portfolio. As you said, they cover all the roles, so the CIO, CFO. And their budgets can be tight. And especially given the last 18 months, if you read some of the data out there, the budgets are really constrained, especially for the SMBs customer. So we try and do, and what our mission is, is what we call creating investment capacity, giving budgets a boost, bringing that vitality to the SMB customer base, to all our customers, but especially SMB customers to help them be able to invest in their digital transformations going forward. So crucial now that all our customers are able to continue to invest in technology. And the pandemic clearly brought at home how important having a digital capability it is. So SMB budgets are tight, and what we try and do is give them that boost, give them that vitality to actually continue to advance ahead and make the right investments for the future. And then from the partners, we actually do a four and a half thousand partners around the world. As you said, partners, they're also not only looking for financial solutions, but how do we differentiate ourselves is to try and help that partner move to a digital platform. We have invested heavily in our digital tools over the last couple of years. So in terms of offering solutions, it can be literally zero touch, low touch so the partner community can plug into our platforms. We also help them on that journey as a service. So technology is moving to as a service. People want to consume technology as a service like they do in the rest of their lives. It's all about subscription. And partners need help to be able to move to another service way. Hopefully GreenLake is the answer. So we support HPE GreenLake's offering. But there's different parts along the way for partners that we look to help them. And last but not least is helping them about asset management. As Brad said, it's all about the assets and understanding how those assets are managed. And helping the partners, having a relevant conversation with their customers as to how best to put in an asset management strategy for their customers. So three areas that we look to differentiate ourselves, Dave. >> We got a lot to talk about. So I want to come back and talk about as a service as well. But Brad, I want to go back to sustainability. So is it just the right thing to do? What's the financial case? Is it good business as well, and where do you fit? >> Yeah, so we believe that sustainability is good for the environment, obviously, but it's also good for business. And when you think about what we bring to the table and those assets back into reuse. So we handle between three and four million assets a year, and over 90% of those, we put back into reuse, with about 10% going into recycling. Putting those back into reuse, the customer that has those assets, we can monetize those assets and help accelerate transformation. So we monetize the asset, and we fund that transition in that transformation so we can really help customers get more budget than they were expecting by leveraging what they would deem to be end-of-life assets, but we find another home for those assets. So it definitely helps customers accelerate the transformation, while being good for the world, good for the environment. >> And that's true, Paul, for SMBs, just maybe on a smaller scale, and definitely makes sense for the channel, right? >> Absolutely. Absolutely. Sustainability now is key. Certainly key for our channel partners is moving from a nice-to-have to a must-have. So absolutely, totally agree. >> Yeah. And it's almost like gain sharing. I mean, sometimes we sell used equipment on eBay. It helps fund future business or future transformation. So let's get into the transformations. Everybody talks about digital transformation. Coming into the pandemic, everybody talked about it, but there was a lot of complacency. We've all seen the wrecking ball and the acceleration we talk about all the time, but what role does HPE Financial Services, and do you have any specific solutions that support digital transformations? Any examples there? Maybe Brad, you could start it off. >> Yeah. Yeah. So I'll start off, and then Paul, feel free to jump in. Look Dave, what I would say is the pandemic taught us that every company is a technology company. And where HPFS comes in is we're looking to provide the investment capacity, which is the lifeblood of a company's digital roadmap. So if you don't have the investment capacity, there is no transformation. So when something like the pandemic comes up, and you can't budget for a pandemic, and revenues are down and budgets are getting squeezed, you really need a partner to help you with that. How do you uncover that investment capacity? So we we've talked to lots of customers. We've also done some research, and the ESG group and analysts basically found that 73% of organizations, not surprisingly, either delayed or canceled projects around IT transformation because of all the uncertainty. So what we're looking to do is leverage all of our capabilities in a timely fashion. Last year, we announced the idea of payment holidays and deferred payments so you could keep your transformation going and not have to pay for it for a full year. And now we look at it as we're coming out of the pandemic. And what we're looking to help customers with is one, help them transition their existing infrastructure into a modernized consumption model like GreenLake. Also looking to accelerate the velocity of the transformation programs by leveraging our capabilities around asset upcycling, as well as our accelerated migration program. And last, looking at our existing customers really doing some financial engineering with them, so they can stretch their budgets more and expand the budget to be able to handle new projects. >> Yeah, I mean, Paul, I think Brad nailed it. You're right, their transformations are strategic. They had to fund VDI initiatives or endpoint security or find some cash to buy laptops to support people at home. People were pulling out their servers and sticking them in their trunk and driving to their home because they couldn't get laptops for awhile. And so what are you seeing now, Paul, particularly in the channel. And of course, again, SMBs were squeezed. Maybe they don't have the liquidity that some of these large public companies have. A lot of people just shored up their balance sheets during the pandemic. Maybe the SMB doesn't have as much advantage to do that. But what are you seeing in regard to the sort of bounce back of spend in more strategic areas like transformation? >> Well, I think what we're seeing right now and what we're hearing, especially for SMB customer, is cash is king. It's all about cash preservation. It's about making sure that... You'll hear some studies where some SMB customers only have three or four months left of cash in their kitty to keep their businesses running. So that is really top of mind now. Would they have to invest? If they don't want invest, they're going to be dead in the water to stay ahead of the competition. So what we're looking to do is really help those customers preserve that cash and reach and look for different ways about how to boost their budget. There's actually nothing better than an example. Brad laid out very nicely in terms of what we can do. Bringing it to life, not so much an SMB customer, but there is UNAD. And UNAD is a university in Columbia based in Bogota. And their mission is very simple, it's all about excellence and learning. But as they went into the pandemic, they needed to invest in their distance learning platforms to really help their students. And like most businesses, cash and budget was being squeezed. Revenues were tight. So it would've been very easy to postpone that investment. Well, what we did with UNAD and working with UNAD under IT team was firstly to understand their existing IT estate and really see what assets are being utilized, what are not being utilized, what assets have reached or ended their useful life. And you'd be amazed. And it's not just the data center, we can work right across their whole estate. So as well as the data center, we look at the PCs. To your point, David, we look at even their print estate. And we identified many, many assets that were being underutilized and other assets that were end of life. So we were able to take those assets back and actually release value and boosts UNAD's budget. And some of those assets could not. They had no value. And sustainability was top of their agenda as well. As you'd imagine, the university wanted to lead and show their students that sustainability is key. So we were able to take those assets back and actually recycle them in a very environmentally sound way. So that was the first step to actually inject some cash into their budgets. The next step then was to look at their existing financial contracts that they had in place where maybe some of their banks and actually restructured those contracts to actually give them additional capacity to invest right now in technology. And I'm delighted to say they partnered with the HPE team, I mean, Aruba, to actually continue their five-year roadmap and actually improved their distance learning platforms. So I just thought that was a really good example right now and in the current climate as to show when we work together with our customers, what's actually possible. >> So let's talk a little bit more about GreenLake. I mean, for decades, I mean, even if I go back to the '80s, I saw financial instruments to sort of rent essentially, but it's different. GreenLake, HPE, has pivoted its entire company to as a service. And I want to understand better what role HPE Financial Services plays in making that transition. It's obviously a crucial part of the financing piece, but Brad, maybe you could tell us a little bit more there. >> Yeah, sure. And I think the great thing about GreenLake is it's more than just a consumption model, it's really providing that cloud experience, on-prem, and being able for customers to really manage a hybrid cloud experience. But where HPEFS plays a role, again, it's around our knowledge and ability around assets. So we are underneath GreenLake, doing financial engineering, managing the assets. But the biggest thing, when you think about how does a customer transition? If they're in a traditional cash purchase paradigm, the cost of change and figuring out how to move into a new type of paradigm and new consumption model can be daunting. So HPFS works closely with our GreenLake team and the customer, and we can take those existing assets and look to accelerate the migration into a GreenLake. A great example of that, a public sector customer, Kern County, they were in that cash paradigm, they had lots of assets. Like most entities, they were under pressure from a budget perspective. Tax revenues were down for a couple years in a row. So not only did moving to a GreenLake model provide some cost savings, and cost savings are important, but it also allowed them to deliver the services they needed to their constituents because they had that pay for use type of flexibility. They didn't have a long delay in procuring and provisioning equipment when they needed to roll something out. And again, once again, HPFS was able to monetize their existing assets, roll those into a GreenLake solution and help self-fund that transformation and really accelerate it to get from that cash paradigm model to a new GreenLake consumption model. >> Paul, what about the channel? I mean, on the one hand, I could see the channels loving GreenLake because there's a lot of services involved, and it's sort of an ongoing drip of cash as opposed to the sort of big hit. But on the other hand, it's the ongoing drip of cash as opposed to the big hit. What's the conversations like with the channel? How is that going? I mean, clearly it's the future, but how do they see it? >> I wouldn't say a drip of cash. We would call it an in-use revenue where it's very predictable, which is actually also a good thing, rather than a sort of a one-and-done solution. So clearly, GreenLake is very important to our channel partners, and we're seeing some really good adoption across the world. Again, we underpin that. The other thing to say is a lot of channel partners, as you likely say, want as sell services and become service providers. And what we also do is support not just the data center, but also workplace and print. And what you'll see on the printing side for many, many years, the print partners have been selling a contractual type of model. But a lot of partners now are moving all of their core portfolio into as a service. And there's different parts. It's nearly a cash to as a service journey, and there's different parts of that ladder on the way. And we will look to help our partners get along that ladder and hopefully position GreenLake. But there's also more simpler solutions like subscription that we can position on that journey. So it's really helping that partner get the confidence and the financial wherewithal and the infrastructure to get on the as a service journey. >> How about solutions? I mean, you guys have had some recent announcements. Maybe Brad, you can take us through sort of what the highlights of those were. >> Sure. So yeah, the first announcement was really the example I just provided, which was how do we transition customers to GreenLake? So again, that's a really important step for many customers, and something that we can help them with is moving from that existing paradigm to GreenLake. The second is really helping customers create velocity to move their transformation programs faster. And we do that in a number of ways, but again, all around the asset in our asset management expertise, whether we look to put those assets back into reuse in their facility, or if we look to monetize those assets and put them into reuse with a different customer. Really, it's all around how do we accelerate the customers transformation as we come out of a pandemic. And then lastly, the offering is really focused on how can we help the customer look at existing budget and really financially engineer where they're spending their money to create new pools of budget and cash so they can fund new projects. So it's interesting because when I look at the customers that we're doing these things with, it really spans every industry. So we're dealing with financial services and insurance companies, communications and broadcasting, travel and hospitality, you name it, manufacturing. So the interesting thing is, while sometimes you come out with solutions that are very industry-specific, I think our circumstances today really span lots of industries, both in the commercial and the public sector. And we're finding that these offers are really relevant right now for customers. >> Let's zoom out for a bit. And Brad, let's start with you, and then Paul, I want to get your unique perspectives from the standpoint of SMB in the channel. Summarize your overall strategy in that context. And then I'm interested in, how important do you feel the HPE Financial Services is with regards... And of course, you guys are biased, but that's okay, I want to hear your bias view. How important is it in the grand scheme of actually doing business with HPE. And I'm interested in in why HPE and how much of a competitive advantage you bring relative to some of your major competitors. >> Yeah, sure. So look, the strategy, in my mind, I'll start with HPFS, it's really making sure that we're working closely with our customers, understanding their needs from a business perspective and what business outcomes they're trying to achieve and then marrying both the financial planning and the technology planning to help those customers deliver and achieve those business outcomes. Doing that, also in a way that is sustainable and is good for the environment and helps customers achieve their sustainability initiatives. So kind of marrying that financial technology and sustainability portion of it. From my perspective, I think HPE is a fantastic partner. One, we've been at GreenLake for quite a while, and it continues to evolve. The experiences that we can provide customers now are significantly advanced from when flex capacity came out years and years and years ago. So I really think if a customer took a look at GreenLake a few years ago, you need to keep looking at it because it really has evolved, really creates a unique experience. But I think it's the combination of our technology. We have great technology in our portfolio. We have a fantastic model in GreenLake, and then we have all of the financial engineering expertise around assets and lifecycles and how to get the most out of your IT investment. And we are a partner. If you have sustainability initiatives, I mean, HPE talks the talk, we walk the walk. We do all of this for ourselves, and then we bring those practices out and share best practices with customers. So I really think it's a great time to partner with HP if you're a customer. >> Right, thank you for that, Brad. Paul, what would you add for your constituents? >> Brad, said it beautifully. So just a couple of points I'd add in. From a partner perspective, we are actually in every corner of the world. So we have that global footprint. And then as you see, consolidation in the market, that's very important, not only for our customers, but also for our partners, more and more solutions are going cross border and involve different regions. And we look to make sure that we're globally consistent in how we work with our partners and work with our customers. And the final thing I'd say is we get very excited about supporting our HPE colleagues. But from a channel perspective, we actually also support HPI, HP Inc. You will recall, before separation, that the companies did. So we also support the workplace and print environments, plus third party vendors, which again, is important for the channel community. Why do you need a one-stop shell? And where you'll often have a mixed technology and the solution. So we're there for that as well and always have been. And I think the partner community love our consistency there >> It's a nice arrow when you quiver. And of course we've seen laptop demand explode. And it looks like it's going to sustain for a while here. It's hard to predict, but Paul, still with you, tell us, thinking about the future, what's getting you jazzed up? >> Well, I said we have a global footprint, and every country is in a different place right now. As we sort of come out of the pandemic, some countries are still in the midst of it. But what gets me jazzed up and what gets me excited is the sense of optimism. I think we're sort of figured out how to navigate our way out of this pandemic and the current environment. And customers all recognize the need to invest in technology. Technology is the way forward. So that means having the capacity, investment capacity, the investment vitality, to make that investment. So what gets me excited is what we do is important and we're there to help. >> Great. Thank you. And then Brad, two-part question for you to bring us home. So what are you excited about, and what do you got going at Discover? >> So in terms of my excitement, I think Paul said it well, every company is a technology company. And when we see that everybody is going through a digital transformation, quite frankly, we at HPEFS are going through our own digital transformation. Paul mentioned earlier about Technomics. We have omni-channel ways of engaging with us that are consistent. We're looking at our customer and partner experience and continuing to improve those. So we're not resting on our laurels in what we've done in the past, we continue to change, to modernize, to create new and better ways of doing business with our customer base. So the exciting part, for me, is that change that comes with innovation and technology. And I just think HPE is a great place to be right now with all of that innovation going on. So you asked about Discover. So we're really excited. We've got a spotlight with Irv Rothman focused on investment agility and key to growth and regeneration. So that's really exciting. We have a few breakouts, making technology a force for good, getting back on track that create the investment vitality to take on the world and investment strategies to accelerate innovation in a disruptive world. So really excited about that. And then last, we've got some demos. We have a live interactive demo on our technology renewal center, as well as some on-demand demos of those renewal centers as well. So we've got a lot going on at Discover, and we're really excited about it. >> Great. Gentlemen, thank you for that. So I mean, look, cost of capital is low, but to have a technology partner with you that's also has financial expertise, that, to me, is a killer combination. Guys, thanks so much for coming on theCUBE. I really appreciate your time. >> Dave, thanks for having us. >> Thanks, Dave. >> All right, and thank you for watching theCUBE's continuous coverage of HPE Discover 2021, the virtual edition. Keep it right there for more great content. (upbeat music)

>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCube and ETR, this is Breaking Analysis with Dave Vellante. >> When a piece of digital art sells for $69.3 million, more than has ever been paid for works, by Gauguin or Salvador Dali, making it created the third most expensive living artists in the world. One can't help but take notice and ask, what is going on? The latest craze around NFTs may feel a bit bubblicious, but it's yet another sign, that the digital age is now fully upon us. Hello and welcome to this week's Wikibon's CUBE insights, powered by ETR. In this Breaking Analysis, we want to take a look at some of the trends, that may be difficult for observers and investors to understand, but we think offer significant insights to the future and possibly some opportunities for young investors many of whom are fans of this program. And how the trends may relate to enterprise tech. Okay, so this guy Beeple is now the hottest artist on the planet. That's his Twitter profile. That picture on the inset. His name is Mike Winkelmann. He is actually a normal looking dude, but that's the picture he chose for his Twitter. This collage reminds me of the Million Dollar Homepage. You may already know the story, but many of you may not. Back in 2005 a college kid from England named Alex Tew, T-E-W created The Million Dollar Homepage to fund his education. And his idea was to create a website with a million pixels, and sell ads at a dollar for each pixel. Guess how much money he raised. A million bucks, right? No, wrong. He raised $1,037,100. How so you ask? Well, he auctioned off the last 1000 pixels on eBay, which fetched an additional $38,000. Crazy, right? Well, maybe not. Pretty creative in a way, way early sign of things to come. Now, I'm not going to go deep into NFTs, and explain the justification behind them. There's a lot of material that's been published that can do justice to the topic better than I can. But here are the basics, NFTs stands for Non-Fungible Tokens. They are digital representations of assets that exist in a blockchain. Now, each token as a unique and immutable identifier, and it uses cryptography to ensure its authenticity. NFTs by the name, they're not fungible. So, unlike Bitcoin, Ethereum or other cryptocurrencies, which can be traded on a like-for-like basis, in other words, if you and I each own one bitcoin we know exactly how much each of our bitcoins is worth at any point of time. Non-Fungible Tokens each have their own unique values. So, they're not comparable on a like-to-like basis. But what's the point of this? Well, NFTs can be applied to any property, identities tweets, videos, we're seeing collectables, digital art, pretty much anything. And it's really. The use cases are unlimited. And NFTs can streamline transactions, and they can be bought and sold very efficiently without the need for a trusted third party involved. Now, the other benefit is the probability of fraud, is greatly reduced. So where do NFTs fit as an asset class? Well, they're definitely a new type of asset. And again, I'm not going to try to justify their existence, but I want to talk about the choices, that investors have in the market today. The other day, I was on a call with Jay Po. He is a VC and a Principal at a company called Stage 2 Capital. He's a former Bessemer VC and one of the sharper investors around. And he was talking about the choices that investors have and he gave a nice example that I want to share with you and try to apply here. Now, as an investor, you have alternatives, of course we're showing here a few with their year to date charts. Now, as an example, you can buy Amazon stock. Now, if you bought just about exactly a year ago you did really well, you probably saw around an 80% return or more. But if you want to jump in today, your mindset might be, hmm, well, okay. Amazon, they're going to be around for a long time, so it's kind of low risk and I like the stock, but you're probably going to get, well let's say, maybe a 10% annual return over the longterm, 15% or maybe less maybe single digits, but, maybe more than that but it's unlikely that any kind of reasonable timeframe within any reasonable timeframe you're going to get a 10X return. In order to get that type of return on invested capital, Amazon would have to become a $16 trillion valued company. So, you sit there, you asked yourself, what's the probability that Amazon goes out of business? Well, that's pretty low, right? And what are the chances it becomes a $16 trillion company over the next several years? Well, it's probably more likely that it continues to grow at that more stable rate that I talked about. Okay, now let's talk about Snowflake. Now, as you know, we've covered the company quite extensively. We watched this company grow from an early stage startup and then saw its valuation increase steadily as a private company, but you know, even early last year it was valued around $12 billion, I think in February, and as late as mid September right before the IPO news hit that Marc Benioff and Warren Buffett were going to put in $250 million each at the IPO or just after the IPO and it was projected that Snowflake's valuation could go over $20 billion at that point. And on day one after the IPO Snowflake, closed worth more than $50 billion, the stock opened at 120, but unless you knew a guy, you had to hold your nose and buy on day one. And you know, maybe got it at 240, maybe you got it at 250, you might have got it at higher and at the time you might recall, I said, You're likely going to get a better price than on day one, which is usually the case with most IPOs, stock today's around 230. But you look at Snowflake today and if you want to buy in, you look at it and say, Okay, well I like the company, it's probably still overvalued, but I can see the company's value growing substantially over the next several years, maybe doubling in the near to midterm [mumbles] hit more than a hundred billion dollar valuation back as recently as December, so that's certainly feasible. The company is not likely to flame out because it's highly valued, I have to probably be patient for a couple of years. But you know, let's say I liked the management, I liked the company, maybe the company gets into the $200 billion range over time and I can make a decent return, but to get a 10X return on Snowflake you have to get to a valuation of over a half a trillion. Now, to get there, if it gets there it's going to become one of the next great software companies of our time. And you know, frankly if it gets there I think it's going to go to a trillion. So, if that's what your bet is then you know, you would be happy with that of course. But what's the likelihood? As an investor you have to evaluate that, what's the probability? So, it's a lower risk investment in Snowflake but maybe more likely that Snowflake, you know, they run into competition or the market shifts, maybe they get into the $200 billion range, but it really has to transform the industry execute for you to get in to that 10 bagger territory. Okay, now let's look at a different asset that is cryptocurrency called Compound, way more risky. But Compound is a decentralized protocol that allows you to lend and borrow cryptocurrencies. Now, I'm not saying go out and buy compound but just as a thought exercise is it's got an asset here with a lower valuation, probably much higher upside, but much higher risk. But so for Compound to get to 10X return it's got to get to $20 billion valuation. Now, maybe compound isn't the right asset for your cup of tea, but there are many cryptos that have made it that far and if you do your research and your homework you could find a project that's much, much earlier stage that yes, is higher risk but has a much higher upside that you can participate in. So, this is how investors, all investors really look at their choices and make decisions. And the more sophisticated investors, they're going to use detailed metrics and analyze things like MOIC, Multiple on Invested Capital and IRR, which is Internal Rate of Return, do TAM analysis, Total Available Market. They're going to look at competition. They're going to look at detailed company models in ARR and Churn rates and so forth. But one of the things we really want to talk about today and we brought this up at the snowflake IPO is if you were Buffet or Benioff and you had to, you know, quarter of a dollars to put in you could get an almost guaranteed return with your late in the game, but pre IPO money or a look if you were Mike Speiser or one of the earlier VCs or even someone like Jeremy Burton who was part of the inside network you could get stock or options, much cheaper. You get a 5X, 10X, 50X or even North of a hundred X return like the early VCs who took a big risk. But chances are, you're not one of these in one of these categories. So how can you as a little guy participate in something big and you might remember at the time of the snowflake IPO we showed you this picture, who are these people, Olaf Carlson-Wee, Chris Dixon, this girl Sono. And of course Tim Berners-Lee, you know, that these are some of the folks that inspired me personally to pay attention to crypto. And I want to share the premise that caught my attention. It was this. Think about the early days of the internet. If you saw what Berners-Lee was working on or Linus Torvalds, in one to invest in the internet, you really couldn't. I mean, you couldn't invest in Linux or TCP/IP or HTTP. Suppose you could have invested in Cisco after its IPO that would have paid off pretty big time, for sure. You know, he could have waited for the Netscape IPO but the core infrastructure of the internet was fundamentally not directly a candidate for investment by you or really, you know, by anybody. And Satya Nadella said the other day we have reached maximum centralization. The main protocols of the internet were largely funded by the government and they've been co-opted by the giants. But with crypto, you actually can invest in core infrastructure technologies that are building out a decentralized internet, a new internet, you know call it web three Datto. It's a big part of the investment thesis behind what Carlson-wee is doing. And Andreessen Horowitz they have two crypto funds. They've raised more than $800 million to invest and you should read the firm's crypto investment thesis and maybe even take their crypto startup classes and some great content there. Now, one of the people that I haven't mentioned in this picture is Camila Russo. She's a journalist she's turned into hardcore crypto author is doing great job explaining the white hot defining space or decentralized finance. If you're just at read her work and educate yourself and learn more about the future and be happy perhaps you'll find some 10X or even hundred X opportunities. So look, there's so much innovation going around going on around blockchain and crypto. I mean, you could listen to Warren Buffet and Janet Yellen who implied this is all going to end badly. But while look, these individuals they're smart people. I don't think they would be my go-to source on understanding the potential of the technology and the future of what it could bring. Now, we've talked earlier at the, at the start here about NFTs. DeFi is one of the most interesting and disruptive trends to FinTech, names like Celsius, Nexo, BlockFi. BlockFi let's actually the average person participate in liquidity pools is actually quite interesting. Crypto is going mainstream Tesla, micro strategy putting Bitcoin on their balance sheets. We have a 2017 Jamie diamond. He called Bitcoin a tulip bulb like fraud, yet just the other day JPM announced a structured investment vehicle to give its clients a basket of stocks that have exposure to crypto, PayPal allowing customers to buy, sell, and Hodl crypto. You can trade crypto on Robin Hood. Central banks are talking about launching digital currencies. I talked about the Fedcoin for a number of years and why not? Coinbase is doing an IPO will give it a value of over a hundred billion. Wow, that sounds frothy, but still big names like Mark Cuban and Jamaat palliate Patiala have been active in crypto for a while. Gronk is getting into NFTs. So it goes to have a little bit of that bubble feel to it. But look often when tech bubbles burst they shake out the pretenders but if there's real tech involved, some contenders emerge. So, and they often do so as dominant players. And I really believe that the innovation around crypto is going to be sustained. Now, there is a new web being built out. So if you want to participate, you got to do some research figure out things like how PolkaWorks, make a call on whether you think avalanche is an Ethereum killer dig in and find out about new projects and form a thesis. And you may, as a small player be able to find some big winners, but look you do have to be careful. There was a lot of fraud during the ICO. Craze is your risk. So understand the Tokenomics and maybe as importantly the Pump-a-nomics, because they certainly loom as dangers. This is not for the faint of heart but because I believe it involves real tech. I like it way better than Reddit stocks like GameStop for example, now not to diss Reddit. There's some good information on Reddit. If you're patient, you can find it. And there's lots of good information flowing on Discord. There's people flocking to Telegram as a hedge against big tech. Maybe there's all sounds crazy. And you know what, if you've grown up in a privileged household and you have a US Education you know, maybe it is nuts and a bit too risky for you. But if you're one of the many people who haven't been able to participate in these elite circles there are things going on, especially outside of the US that are democratizing investment opportunities. And I think that's pretty cool. You just got to be careful. So, this is a bit off topic from our typical focus and ETR survey analysis. So let's bring this back to the enterprise because there's a lot going on there as well with blockchain. Now let me first share some quotes on blockchain from a few ETR Venn Roundtables. First comment is from a CIO to diversified holdings company who says correctly, blockchain will hit the finance industry first but there are use cases in healthcare given the privacy and security concerns and logistics to ensure provenance and reduce fraud. And to that individual's point about finance. This is from the CTO of a major financial platform. We're really taking a look at payments. Yeah. Do you think traditional banks are going to lose control of the payment systems? Well, not without a fight, I guess, but look there's some real disruption possibilities here. And just last comment from a government CIO says, we're going to wait until the big platform players they get into their software. And so that is happening Oracle, IBM, VMware, Microsoft, AWS Cisco, they all have blockchain initiatives going on, now by the way, none of these tech companies wants to talk about crypto. They try to distance themselves from that topic which is understandable, I guess, but I'll tell you there's far more innovation going on in crypto than there is in enterprise tech companies at this point. But I predict that the crypto innovations will absolutely be seeping into enterprise tech players over time. But for now the cloud players, they want to support developers who are building out this new internet. The database is certainly a logical place to support a mutable transactions which allow people to do business one-on-one and have total confidence that the source hasn't been hacked or changed and infrastructure to support smart contracts. We've seen that. The use cases in the enterprise are endless asset tracking data access, food, tracking, maintenance, KYC or know your customer, there's applications in different industries, telecoms, oil and gas on and on and on. So look, think of NFTs as a signal crypto craziness is a signal. It's a signal as to how IT in other parts of companies and their data might be organized, managed and tracked and protected, and very importantly, valued. Look today. There's a lot of memes. Crypto kitties, art, of course money as well. Money is the killer app for blockchain, but in the future the underlying technology of blockchain and the many percolating innovations around it could become I think will become a fundamental component of a new digital economy. So get on board, do some research and learn for yourself. Okay, that's it for today. Remember all of these episodes they're available as podcasts, wherever you listen. I publish weekly on wikibon.com and siliconangle.com. Please feel free to comment on my LinkedIn post or tweet me @dvellante or email me at david.vellante@siliconangle.com. Don't forget to check out etr.plus for all the survey action and data science. This is Dave Vellante for theCUBE Insights powered by ETR. Be well, be careful out there in crypto land. Thanks for watching. We'll see you next time. (soft music)

>> Announcer: From theCUBE Studios in Palo Alto and Boston, connecting with thought leaders all around the world, this is a CUBE Conversation. >> Hey, welcome back, everybody. Jeff Frick here with theCUBE coming to you from our Palo Alto studios for a CUBE Conversation. We're talking about the Citrix Workspace Summit. It happened earlier today. And we've got one of the experts in the field, CUBE alumni and always a really fun guest to have on. Let's give a welcome to Tamara McCleary. She's coming to us from Colorado. She's the CEO of Thulium but you know her from social media and seeing her at all the conferences and speaking. And Tamara, it's great to see you again >> Jeff, it's so good to be here. Hey, next best thing to being in person, right? >> Absolutely. I mean, there is some good stuff. Neither of us had to get on an airplane today and we were able just to connect via the magic of the internet, which I think people forget how magic it truly is. So I looked up, we last spoke, it was mid-April. We were about a month into this thing after the kind of shutdown. And really the topic there was about this light switch moment on the work from home front. Now we're seven months into this, eight months into this, and clearly it's not going away anytime soon. And even when it does, it's not going to go back exactly to the way it was. So first off, how are you doing? 'Cause I know you spend a lot of time at conferences and traveling all over the world, so your life's been changed quite a bit. And then two, just your kind of perspective as we've moved from the light switch moment to the, that this is the new normal and will be the new normal going forward. Maybe not exactly how it is today, but we're not going back to the way that it was before. >> You couldn't be more spot on, Jeff. In fact, when you said April, to me, it almost feels like not seven months. It feels much longer ago. And since the last time I got on an airplane was the end of February, and that was a huge disruption to me in my life. I had always been in three, four cities a week, every week, and haven't traveled on an airplane since February. So the world is different, and it has shifted, and there's no going back. We can't step in the river twice and hit that same spot. I totally messed up that quote, but that's me. You're used to that already. >> Jeff: Exactly. >> But some things don't change. But I think when we look at work, and what we were talking about back in April is that now we're looking at the potential for kind of a hybrid approach, whether we're talking about work or even kids, some kids going back to school, there's a hybrid approach. And with that comes its own set of complexities that we have to consider. So not only has the culture shifted into a place where you have your workforce who has gotten used to working remotely, and there's a lot of things with working remotely that we didn't have when office was the centrical focus for the workplace. So there's a lot of flexibility when you work from home. And I think one of the interesting things with the Citrix Workspace Summit was when CEO David Henshall talked about how it's the people, right? So it's our workforce, our employees who are our most valuable, but also our most costly assets. So we have to make sure that the employee experience is one that is pleasing and helps us to have not only talent acquisition, but also talent retention in a really dynamic, competitive atmosphere. And I'm sure I just posed this question so we could go a million different places with this. Where do you want to go with it, Jeff? >> Well, I was going to say, and of course we can go forever, and we don't have forever, so at some point we'll have to stop talking at the end of this interview. But I just love having you on. And what I want to drill in is as we've talked about the new way to work for a very, very long time. This is not a new topic. And we've had remote work tools and we've had VPNs and we've had mobile phones now since 2007, but we didn't have this forcing function, and I think that's what's really different here is that now it wasn't a choice anymore. There was no more planning and talking about it and maybe or maybe not. Work from home was kind of a first-class citizen in terms of priority. COVID changed all that dramatically overnight. And it's driven home this other kind of concept which we talk a lot about generically in terms of the customer experience as they interact with our applications, which is the way that now they actually interact with the company. And we've talked a little bit about new way to work, but now it's really driven to the forefront, because as you said, there's a lot of benefits from working from home. You could eat dinner with your family, maybe can pick up a few more of the kids' activities, whether it's a sports game in the middle of the afternoon or something in the evening, but there's also a lot of stress. There's a lot of kind of this always on and this constant notifications, whether it's coming from email or text or Slack or Teams or Asana or whatever. So refocusing on the employee experience and elevating that up into a much more important thing, as you said, for both wellness and employee satisfaction, but also retention and getting new employees. It's really changed the priority of that whole set of, kind of point of view around the employee experience that wasn't there kind of pre-COVID. >> Absolutely. And I think you just tapped onto something that I think affects all of us who are juggling these multifaceted lives, and that is the constant interruption and distraction, and that costs money. And I think about that as the CEO of our organization is that how many of these distractions could be avoided to create efficiency and productivity. It also creates happiness for the individual. I don't think anybody likes to be constantly distracted, but when you have a bunch of different applications and you don't have them in one accessible place and you're constantly having to flip between these applications, it can cause a lot of friction and frustration. And I think genuinely that was my very first introduction to Citrix was the ability to really streamline and have everything in one place on a beautiful dashboard that was personalized to the individual. Not everybody in the organization needs to have all the applications, right? Some of your employees only need a few, and it just depends on who they are and what they're doing within the organization. And so I think decreasing that friction, making it easier for people, and certainly ensuring not only a frictionless experience at home but also ensuring security is huge. I mean, how many times have we talked about cybersecurity is not a bolt on afterwards. It has to be all the way up through the stack. And certainly we did have an increased threat landscape with work from home situations because there were all these security breaches and issues and vulnerabilities. So I know we're not talking security today, but I'm wild about it. But I think that all of these things, what I like about what Citrix is doing, and I enjoy the Summit, is the fact that they're blending everything into a single solution so that it just gets done. Work gets done from wherever you are, whether you're at home, you're in office, or in your car, work gets done. >> And not only work but I thought the theme that's interesting that came out in David's keynote is our best work. It's good work and high-value work. And there's really kind of two aspects of that. One, as you just said, is please help me with the distractions and use machine learning and artificial intelligence and this unified platform to decide whether I should or should not be distracted. Also help me prioritize what I should be working on kind of right now, which, again, a great opportunity for AI and ML to elevate that which is most important to the top of my inbox. But even more in one of the keynotes was integrating the concept of wellness, and not just wellness in the HR manual at the back after vision and dental and getting your health checks, but wellness even where the application suggests that you take a two-hour window in this particular period of time to be thoughtful and do some deep thinking. And someone mentioned the people we talk about in automation and getting rid of drudgery and errors and all the bad stuff that comes from doing crappy work, not only is it not fun, but super error prone. This is a really different to use technology to help the employee, as you said, not only just get work done, but get good work done, get high-value work done, prioritize good stuff, and not just deal with the incessant henpecking that is the notification world that it's really easy to fall into if you don't turn some of that stuff off or at least tone them down a little bit. >> That's so true. I don't know if you saw this, but there a study by Stanford of, I think it was 16,000 workers, and over a nine-month period, they did this study, and it was a study looking at work from home and whether productivity was increased. And every, 'cause at first you remember what it was, Jeff. I mean, in the old regime, we would thought, oh dear, we don't want a remote workforce because everybody's going to be hanging out in their pajamas and screwing around and not doing work. And that's not true. What ends up happening is that this study showed that productivity increased by 13%. And, I mean, that's huge, right? So there was a huge bump in performance. And in this particular study, the variables that they cited was perhaps that they had a quieter workspace. I mean, you're not getting barraged by all the endless meetings, unless you have endless Zoom meetings, but that's a whole nother conversation. But you're having more time to focus and flexibility on when you work, which also increases focus. But I thought what you mentioned, the wellness piece was important, because then if you look at other studies, there was a Forbes article that cited that the average worker starts at 8:32 a.m. or something like that and works until 5:38 p.m. And I think the days of the week that were the most productive were Tuesday, Wednesdays, and Thursdays. But this was interesting, I thought. Telephone calls were up by 230%, so the calls that employees were making, and CRM activity was up by 176% and email up by 57% and chats up by 9%. So what we're seeing is that people are trying to find creative ways to remain connected and communicate, but in different ways. And I think that's where the wellness piece comes in and kind of what you were saying with that. I think it's a microapp that Citrix has on their Workspace, their workspace dashboard that pops up a reminder and says, hey, you think you should take a break or get up from your desk. But I think that what's nice about that is it's easy to get sucked into your computer all day. I'm guilty. I will definitely say I can start off pretty darn early in the morning or usually around by five and go till late at night. But, and it's all in front of the computer screen. So maybe I need that Citrix workspace solution to tap me on the shoulder and tell me to go take a meditation break. >> At least one of those watches that'll tell you to get up and twist around. Well, let's shift gears a little bit. They had Satya Nadella on, and Satya is a phenomenal executive, been super successful turning that big, very large boat, Microsoft, into really a cloud company and a SaaS company, and nothing but great success. Always happy to hear him. He had some interesting comments I want to run by you. One of them he said is we were dogmatic about work before, but don't replace what we were with just a new dogma. And what he really highlighted, A, obviously without the technology platform and cloud and all these tools that we have in place, this couldn't have happened. But more importantly, he said it really highlights the need for flexibility and resiliency, and to really, again, kind of elevate those as the first class citizens as to what you should be optimizing for. And really the highlight within this sudden shift with COVID that if you've got those capabilities, you're going to be successful, and if you don't, you're in real trouble >> I'm glad you brought Satya up, because he also said something really cool that I think is true, and that is we are running right now, currently we are running a global scale experiment. Do you remember him saying that? >> Yeah. >> And it's so true. I think right now the social scientists are going wild because finally they've got their captive collection of their study, their guinea pigs. But the other thing he was saying, too, is that we're going to be harnessing all these technologies to be able to re-skill and up-skill. And how long have we been talking about this, Jeff, with the future of work, that it will be a re-skilling and up-skilling of the workforce. He even mentioned holographic technology. He didn't go into it, but just the mention of it got me thinking about how we are currently using some of those nascent technologies to be able to up-skill and re-skill our workforces and also protect a workforce that doesn't necessarily need to be on scene on the edge of it all. And then he gave an example of an engineer being able to communicate with a first-line worker without having to be actually in the physical presence. And so I think this crucible that we're in called a global pandemic, forcing our hand, really, to do all the things that we've been talking about at all these conferences that we've been to, for me, maybe the past two decades, is that it's show, don't tell. So we're not talking about it anymore. We actually have to do it. And another thing that Satya said was that nine to five is definitely not true anymore with work. It's flexibility. And it's really... He also mentioned this EEG study into meeting fatigue. >> Jeff: Yes. >> I thought it was pretty wild. An EEG study into meeting fatigue. And I bet even without reading that study, all of us who are on video conferencing systems can probably tell what the outcome of that was. But concentration wanes very quickly. In fact, I think in that study it was after 20 minutes. But, so kudos to Citrix for putting on their summits, because did you notice for once we had the enjoyment of all these just really contents, deliciously packed segments that were short. >> Jeff: Right. >> Whereas at live events, they went on way too long. I mean, even customer stories went on way too long. And I really love the staccato nature of these customer stories and partnerships and what was working, and I just thought that they did a really nice job, and it was interesting because it met perfectly with staying underneath that 20-minute window before attention wanes. >> Right, right. And they even broke it up into three conferences, right? It was Citrix Synergy before. >> Right. >> Now it's workspaces, it's cloud, and then the third one will be security. But I want to double down on another concept. We talked about it last time with you and with Amy about measuring work and about kind of old work paradigms in terms of measuring performance that were really based more on activity than output. And this concept that work is an output, not a place. And it kind of makes you think of talking about cloud and a cloud-centric way of thinking about things. It's not necessarily the delivery method. It's about adopting quick change and rapid pace and having everything available that you need anywhere you are at the same time. So it seems strange to me that it took this to drive people to figure out that they should be measuring output and not activity. And were some early applications that came out when this all went down that are going to report back as to how often are you looking at your Zoom calls and how often are you sitting in front of your desk and all this silly stuff that just, again, misses the point. And I think this whole employee experience is, as you said, make 'em happy, make 'em feel fulfilled. They want to do meaningful work. They want to do high-value work. They just don't want to be an integration machine between the email system and the accounts receivable system and the accounts payable system. There's so much of an opportunity to get more value from the people, which, oh, by the way, makes for happier people. So do you think finally we're at a point where we can start getting away from just measuring activity unless that's your job to put a widget on a screw and really focus on output and high-value output and innovative output and deep thinking output versus just checking another box and passing the paper down the line? >> You know, Jeff, that reminds me of what Erica Volini, I think she's global human capital practice at Deloitte. I really loved her presentation. I also like the fact that I felt like she was speaking from her home, and she mentioned she's a new mom, and so there was this warmth and connection there which also I think is something really that we don't think about being, but it is a gift since we've all had to work from home is being able to see kind of executive individuals in a regular environment, and it humanizes it all, right? She said something really interesting in her talk. She was talking about rearchitecting the future of work, and she was talking about essentially, the premise was that human beings need, crave, have to have work that's meaningful and real. And part of this whole experience piece, part of this removing the friction from the experience of the employee and providing opportunities, stimulating growth opportunities for employees to give them that sense of meaning. But also she talked about the relationships. I mean, work is a huge part of the relationships in our life. And so this meaningful relationships and connections and in her architecting the work of the future, it's harnessing technology in service to humans to do a better job. And I think the word she used was augmentation, right? So the augmentation piece would be as we think about reinventing or re-imagining or re-architecting, we look at what's going to happen when we have the human working with the machine, but the machine in service to augmenting that human being to do, potential is what she was talking about, to really reach their potential. And so it's not about being replaced by technology. It's not being replaced by artificial intelligence, with machine learning algorithms. It's actually working in tandem so that technology potentiates the human that is using the technology. And I think that was a really good way of putting it. >> Right, right. I mean, we talk, it's one of our taglines, right? To separate the signal from the noise. And the problem is with so many systems now, and I forget, you may know off the top of your head, the average number of applications that people have to interact with every day to get their job done. >> Too many. >> Too many. >> Too many. >> It's a lot. So, so there is a lot of noise, but there's also some signal. And so if you're not paying attention, you can miss the signal that might be super, super important because you're overwhelmed by the noise. And so I think it is a real interesting challenge. It's a technology challenge to apply the machine learning and artificial intelligence, to sort through the total flow, to be able to prioritize and separate the signal from the noise to make sure we're working on the stuff that we should be working on. And I think it's a growing challenge as we just seem to always be adding new applications and adding new notifications and adding new systems that we have to interact with versus taking them away. So Citrix has this approach where we're just going to bring it all in together under one place. And so whether it's your Salesforce notification or your Slack notification or Zoom meeting, whatever, to have it orchestrated as a single place so I don't have 18 tabs, 14 browsers, and two laptops running just to get my day job done. >> You're going to make me self-conscious of all the tabs I have right now. Thanks a lot, Jeff. But, it's kind of, I like hearing stories, right? I think stories communicate to me kind of these practical applications. And I think Citrix did a brilliant job in the Workspace Summit of highlighting some of these customer stories that were really inspiring during the pandemic. One of 'em was City National Bank and Ariel Carrion? This is a test of my memory. He's the CTO, right, of City National Bank. And he's talking about that they had already had a partial migration to the cloud prior to the pandemic. So obviously there was an advantage for those organizations that already had their toe in the water. So, but when the pandemic hit, then it really catalyzed that movement all the way into the cloud and essentially creating a digital bank. And what was really interesting to me is that they funded 9600 loans and taking on new clients during that time of transformation to a digital bank. And one of the coolest things that he said to me was that in a regular program, it would've taken, mind you, get this. It would've taken 14 years, 14 years to accomplish what they did in three months. >> That's a long time. >> I was blown away, right? Just to me, that speaks a lot, because what we're talking about here is their clients are small business, and who do you think was impacted most during the pandemic? Small business. So the ability to get loans was critically important to the survival of a lot of companies. And the same story they had with eBay and David Lessor was talking, he's a senior manager in the office of the CIO, I think I remember. And he was talking about how obviously eBay is a digital platform, right? But if you think about the pandemic when we were all had these shelter in place orders, lots of people were able to still make money and earn a living because they were able to do business on eBay. And both eBay and City National Bank are obviously customers of Citrix. But I just found this to be really inspiring, because for eBay pre-pandemic, it was like, I don't know. I think they said they had 11,000 connected users prior to the pandemic, and a lot of those were in physical call centers. >> Jeff: Right. >> And then post-pandemic, I think he was reaching, saying end of Q4 was going to be something like 14,000 connected users. That's huge from 11 to 14. >> Yeah. >> And again, to your point, it's kind of forcing our hand into really not only pivoting, but increasing our speed in this ever-changing dynamic environment. >> Right. >> You know, one of the other things that came up, before I let you go, that it's always nice to have frameworks. Sometimes it just helps us organize our thoughts and it's kind of a mental cheat sheet. And they talked about the four Cs, connectivity, content, collaboration, and culture. And I would have to say they're in inverse order of how I would potentially have prioritized them. But I just wanted to zero in on the culture piece, 'cause I don't think people focus enough on culture. And one of the things I think we talked about in April, and I've certainly talked about a number of times going through this thing in leadership in these crazy times is that the frequency and the type and the topics in communication within your internal world have gone up dramatically. I think we had the, we had a CMO on the other day, and she said internal comms, this is a big company, prior to COVID was important, but not that important within the list of the CMO's activity. But then once this thing hit, right, suddenly internal communications, again, in terms of frequency and the types of topics you're talking about and the forums that you talk about and the actual vehicles in which you talk about, whether it's a all hands Zoom call or it's more frequent one-on-ones with your manager, really, really increase the importance of culture, and then I think probably is going to show over time the people that have it right, getting some separation distance from the people that got it wrong. I wonder if you could just talk about, 'cause you're a big culture person and you know how important the people part of the whole thing is. >> Yeah, culture drives everything. You're right. And that was Citrix's CIO who gave those four Cs, I think, Meerah Rajavel. >> Yeah, yeah. >> She gave those four Cs. And you couldn't be, you couldn't have tapped into something that I think is the soft underbelly of the organization, which is what is the culture. And anyone who's worked in an organization with a sick culture knows that it's just, it's cancerous, right? It grows and it causes decay. And I don't care how much innovation you have. If the culture is sick, you just, you're going to lose your best people. It's hard to work in a sick culture. And so I think what we had to do is when we all started working remotely, that was a culture shift, because we were siloed off of it. We weren't actually hanging out in physical space. Some of the things that we enjoyed about meeting with other human beings physically changed. And so it really behooved organizations to take a look at how they were going to foster culture digitally, how they were going to create that sense of bonding between not only those within your departmental area, but cross over into other areas. And I think that creating that culture that says I don't have to be in the exact same physical space, but we can still connect. I mean, you and I are doing this. We're not in the same physical space. >> Jeff: Right. >> But I'm still going to feel like we met today. >> Jeff: Right. >> You can create that for your employees. And it also means that we learned that we don't have to be in that same physical space, right? And I thought that was a really interesting position when Hayden Brown, the CEO of Upwork, was talking at the summit and saying that even when we look at creating culture with employees who aren't necessarily, maybe it's a workforce from all over the world that you're using, a remote workforce. And when you're using things like employees, if you've got work to do and you can find a really good talent and you can grab them for what it is that you need, you're actually increasing your ability to be able to deliver on things versus having to worry about whether you have that person in house, but you still can create that culture where everyone is inclusive, where someone can be in Australia and someone's in San Francisco and someone's in the UK, and you still have to create a cohesive, inclusive culture. And it matters not anymore whether or not you are a full-time employee or if you're a contract worker. I think in today's space, and certainly in those future of work conversations, it's more about, to the very first thing you said at the beginning, it's more about output. How's that for tying it back up again? >> Jeff: Yeah, very good. >> And that was totally unplanned. But it is about output, and that's going to be the future of work culture. It's not going to be the title that you have, whether or not you're a full-time employee or a part-time employee or a contract worker. It's going to be who are you meeting with? Who are you having these digital interfaces with and Slacking with or using any sort of platform application that you want to use. It's remaining in touch and in communication, and no longer is it about a physical space. It's a digital space. >> Right, right. All right, well, I'm going to give you the last word. You are a super positive person, and there's reasons, and for people that haven't watched your TED Talk, they should. I think it's super impactful and it really changed the way I look at you. So of all the negatives, wrap us up with some positives that you see as we come out of COVID that going through this experience will make in our lives, both our work lives as well as our personal lives. >> Well, since you're going to allow me to go deep here, I would say one of the things that COVID has brought us is pause. It caused us to go in. And with any dark night of the soul, we have to wrestle with the things that are real for us, and the things that fall away are those that were false, false perceptions, false ideas, illusions of even thinking who we are, what we're doing. And we had to come home to ourselves. And I think one of the things that COVID gave us through uncertainty was finding a center in that uncertainty. And maybe we got to know our beloveds a bit more. Maybe we got to know our kids a bit more, even if they drive us crazy sometimes. But in the end, I think maybe we all got to know ourselves a little bit more. And for that, I think we can harness those seeds of wisdom and make better choices in the future to co-create together a future that we are all pleased to wake up in, one that is fair, one that is equal, one that is inclusive, and one that we can be proud to have contributed to. And that's what I hope we've taken from this extremely hard time. >> Well, Tamara, thanks for sharing your wisdom with us. Really appreciate it. And great to see ya. >> Good to see you, too, thank you. >> All right, she's Tamara, I'm Jeff. You're watching theCUBE. Thanks for watching. We'll see you next time. (bright music)

>>Trump and low park California in the heart of Silicon Valley. It's the cube covering cloud now. Awards 2020 brought to you by Silicon angle media. Now here's Sonya to garden. >>Hi and welcome to the cube. I'm your host Sonia to Gary. And we're on the ground at Facebook headquarters in Menlo park, California covering cloud now's top women entrepreneurs in cloud innovation awards. Joining us today is modest to get day, the cofounder of branch motto. Welcome to the cube. Thank you so much for having me. So you're receiving an award today for being a top female entrepreneur in cloud innovation. How does that feel? >>It feels awesome. I'm humbled to be in such amazing company with some great ladies that have started really great companies, so pretty excited to be here. >>Great. So just give us a brief overview of your background. >>Sure. Uh, my background, well, I probably don't have the regular Silicon Valley background. I was born and raised in communist Romania, uh, in a pretty small town called Barco, uh, in the Rijo Romania called Moldavia. I was very good at math. Um, and my parents, uh, pushed me to explore applying to schools in the United States, which I did. Um, and I applied to 23 colleges and the DOB, uh, getting a full scholarship from Cornell where I studied computer engineering. Um, I dreamt of working for big companies, which I did for a while, uh, until one day when I remember I was doing a master's to Stanford and one professor told me I was, I told him, I was like, I don't think I could ever start a company. And he was like, what if you don't? Like, who do you think? Well, so I was like, Oh, I never thought about it that way. Um, and that's when I think my entrepreneurial dream started. And a few years later I started, um, phone co-founders and started a few different companies that eventually ended up being branch. That's a long answer to your question. >>No, that's perfect. So what inspired you to start branch and how did you navigate getting funding? >>Um, it's a, it's an interesting story. I think we came together, my cofounders and I were in business school, Stanford, we all want to start a company and we did what all business school students do. We just started something that sounded cool but maybe it didn't have such a big market. Um, and uh, then pivoted and ended up building an app. So we worked on an app or the mobile photo printing app called kindred. We worked on the Apple for quite some time. It was, um, over a year we sold over 10,000 photo books. I've seen a lot of images of babies and pets and we reviewed manually every single book and we had a really hard time growing. So if you think about the mobile ecosystem today, and if you compare it to the web on the web, the web is a pretty democratic system. >>You, um, you have the HTTP protocol and you are able to put together a website and make sure that the website gets found through social media to research to all this other platforms. Apps are much harder to discover. Um, the app ecosystem is owned by the platforms. And we had a really hard time applying. I was coming from the web world and all the things I had done to market websites just in the work with the apps. And it was hard. Uh, you know, you could only Mark at the top and how out all the content inside the app. That's a lot more interesting than the app itself. So we, we felt that we were like really, really struggling and we would need it to kind of shut the company down. And then we realized that one of the things that we were trying to build for us to a disability to allow people to share and get to content within the app, which is in our case was photo books was actually something that everyone in the ecosystem needed. >>So we, we asked a lot of people and it seemed like this was a much bigger need. Uh, then, you know, the photo books. And, uh, we had started to already build it to solve our own problem. So we started building a linking and attribution platform, um, to help other app. And mobile companies grow and understand their user journey and help build like interesting connections for the user. So, you know, our mission is to, um, to help people discover content within apps, uh, through links that always work. Uh, and it's been a wonderful, like an F pretty exciting journey ever since. That's really inspiring and, and solving a real world problem, a real world problem. >> So it's interesting when you ask about fundraising. Uh, it was so hard to raise money for the photo book app. And we raised actually from, uh, uh, pay our ventures and they actually, even now I remember, uh, the guy patch man sat us down in a very Silicon Valley fashion at the rosewoods and was a very hot day and there was like Persian tea being served and he gave us money and he said, you know, I just want to do something. >>I am not investing in the idea. I'm investing in you as a team. Uh, and if you pivot away from photo books, you know, uh, which we did and I think we pivoted the way because we ended up finding a much, much bigger problem. And we felt that, you know, we could actually make a, an actual change into the mobile cloud ecosystem. And that's how, that's how it all started. Uh, and it wasn't actually was easier to raise money after we had a really big problem. We had a good team that had been working together for almost two years. We had product market fit. >> So, uh, so yeah. So what are some things that have influenced you in your journey to become an entrepreneur? Um, some things interesting. Um, well I would say the Stanford design school. Um, I think I came from working for Siemens, which is a giant company. >>And I started doing this project and I remember one of the projects was we built, um, an, uh, a toolbar we were supposed to where we're doing a project for, um, Firefox, which, you know, Mozilla was utilize browser, uh, which was in some ways the precursor to Chrome. And we're trying to help it grow. And we didn't know. And one of the ideas was we, we built this toolbar for eBay and eBay hadn't had a toolbar for Firefox. And we, you know, we were some students for two weeks. We build this toolbar bar and then someone bought the car to our toolbar. And I was like, wow. Like how incredible is it that you can just kind of put your thoughts on something and just get something done and make an actual impact someone's life. And I think that's when the spark of the entrepreneurial spark, it was during that time that, um, Michael Dearing course, a professor and one of my D school courses also told me the thing that if I don't do it, who will? >>And I think that's when, that's when it all started. I think the things that have helped me along the way, I mean, my cofounders, I think I've been incredibly lucky to find cofounders that are incredibly eager to be good at what they do and also very different from me. So I think if you think about why many companies implode, it's usually because of the founding team. We've been together for almost seven years now. Uh, and it's been an interesting way to find balance through so many failed companies. So many stages of growth branches over 400 people now. So you know, our roles have shifted over time and it's been like, uh, an interesting journey and I think recently more in the past few years, I think one of the things that has helped me find balance has been having a group of female founder friends. Um, it's really interesting to have a peer group that you can talk about things with and be vulnerable with. >>And I didn't have that in the first few years and I wish I did. My cofounders are amazing, but I think in some ways we are also coworkers. So having an external group has been incredibly helpful in helping me find balance in my life. So I think a lot of women feel that way. They feel that it's really difficult to navigate in this male dominated workspace. So what advice would you give to female entrepreneurs in this space? Yeah, I mean it is really hard and I think confidence is something that I've noticed with myself, my peers, the women that I've invested in. I do investing on the side. Uh, I would say believe that you can do it. Uh, believe that the only, the sky's the limit believe that, um, you can do more than you think you can do. I think sometimes, uh, you know, our, our background and the society around us, um, doesn't necessarily believe that we can do the things that we can do as women. >>So I think believing in ourselves is incredibly important. I think the second part is making sure that we build networks around us. They can tell us that they believe in us. They can push us beyond what we think is possible. And I think those networks can be peers. Like my funeral founder group, we call each other for ministers or, uh, I think investors. Um, I think it can be mentors. And I've had, I've been lucky enough to have amazing women investors, uh, women mentors. Um, and I, it's been a really incredible to see how much they helped me grow. So I think the interesting thing is when I was just getting started, I didn't look for those communities. I didn't look for a guy. I just kinda felt, Oh, I can do it. But I didn't actually realize that being part of a community, being vulnerable, asking questions can actually go help me go so much further. Um, so the advice would be to start early and find a small group of people that you can actually rely on, and that can be your advocates and your champions. So, yeah. Well, thank you so much for those words of wisdom. Thanks for having me. Thank you for being on the cube. I'm your host, Sonia to Gary. Thanks for watching the cube. Stay tuned for more.

>> Announcer: From our studios, in the heart of Silicon Valley, Palo Alto, California, this is a CUBE conversation. >> Hello, and welcome to theCUBE studios, in Palo Alto, California for another CUBE conversation where we go in depth with though leaders driving innovation across tech industry. I'm your host, Peter Burris. The whole concept of self service analytics has been with us decades in the tech industry. Sometimes its been successful, most times it hasn't been. But we're making great progress and have over the last few years as the technologies matures, as the software becomes more potent, but very importantly as the users of analytics become that much more familiar with what's possible and that much more wanting of what they could be doing. But this notion of self service analytics requires some new invention, some new innovation. What are they? How's that going to play out? Well, we're going to have a great conversation today with Stephanie McReynolds, she's Senior Vice President of Marketing, at Alation. Stephanie, thanks again for being on theCUBE. >> Thanks for inviting me, it's great to be back. >> So, tell us a little, give us an update on Alation. >> So as you know, Alation was one of the first companies to bring a data catalog to the market. And that market category has now been cemented and defined depending on the industry analyst you talk to. There could be 40 or 50 vendors now who are providing data catalogs to the market. So this has become one of the hot technologies to include in a modern analytics stacks. Particularly, we're seeing a lot of demand as companies move from on premise deployments into the cloud. Not only are they thinking about how do we migrate our systems, our infrastructure into the cloud but with data cataloging more importantly, how do we migrate our users to the cloud? How do we get self-service users to understand where to go to find data, how to understand it, how to trust it, what re-use can we do of it's existing assets so we're not just exploding the amount of processing we're doing in the cloud. So that's been very exciting, it's helped us grow our business. We've now seen four straight years of triple digit revenue growth which is amazing for a high growth company like us. >> Sure. >> We also have over 150 different organizations in production with a data catalog as part of their modern analytics stack. And many of those organizations are moving into the thousands of users. So eBay was probably our first customer to move into the, you know, over a thousand weekly logins they're now up to about 4,000 weekly logins through Alation. But now we have customers like Boeing and General Electric and Pfizer and we just closed a deal with US Air Force. So we're starting to see all sorts of different industries and all sorts of different users from the analytics specialist in your organization, like a data scientist or a data engineer, all the way out to maybe a product manager or someone who doesn't really think of them as an analytics expert using Alation either directly or sometimes through one of our partnerships with folks like Tableau or Microstrategy or Power BI. >> So, if we think about this notion of self- service analytics, Stephanie, and again it's Alation has been a leader in defining this overall category, we think in terms of an individual who has some need for data but is, most importantly, has questions they think data can answer and now they're out looking for data. Take us through that process. They need to know where the data is, they need to know what it is, they need to know how to use it, and they need to know what to do if they make a mistake. How is that, how are the data catalogs, like Alation, serving that, and what's new? >> Yeah, so as consumers, this world of data cataloging is very similar if you go back to the introduction of the internet. >> Sure. >> How did you find a webpage in the 90's? Pretty difficult, you had to know the exact URL to go to in most cases, to find a webpage. And then a Yahoo was introduced, and Yahoo did a whole bunch of manual curation of those pages so that you could search for a page and find it. >> So Yahoo was like a big catalog. >> It was like a big catalog, an inventory of what was out there. So the original data catalogs, you could argue, were what we would call from an technical perspective, a metadata repository. No business user wants to use a metadata repository but it created an inventory of what are all the data assets that we have in the organizations and what's the description of those data assets. The meta- data. So metadata repositories were kind of the original catalogs. The big breakthrough for data catalogs was: How do we become the Google of finding data in the organization? So rather than manually curating everything that's out there and providing an in- user inferant with an answer, how could we use machine learning and AI to look at patterns of usage- what people are clicking on, in terms of data assets- surface those as data recommendations to any end user whether they're an analytics specialist or they're just a self- service analytics user. And so that has been the real break through of this new category called data cataloging. And so most folks are accessing a data catalog through a search interface or maybe they're writing a SQL query and there's SQL recommendations that are being provided by the catalog-- >> Or using a tool that utilizes SQL >> Or using a tool that utilizes SQL, and for most people in a- most employees in a large enterprise when you get those thousands of users, they're using some other tool like Tableau or Microstrategy or, you know, a variety of different data visualization providers or data science tools to actually access that data. So a big part of our strategy at Alation has been, how do we surface this data recommendation engine in those third party products. And then if you think about it, once you're surfacing that information and providing some value to those end users, the next thing you want to do is make sure that they're using that data accurately. And that's a non- trivial problem to solve, because analytics and data is complicated. >> Right >> And metadata is extremely complicated-- >> And metadata is-- because often it's written in a language that's arcane and done to be precise from a data standpoint, that's not easily consumable or easily accessible by your average human being. >> Right, so a label, for example, on a table in a data base might be cust_seg_257, what does that mean? >> It means we can process it really quickly in the system. >> Yeah, but as-- >> But it's useless to a human being-- >> As a marketing manager, right? I'm like, hey, I want to do some customer segmentation analysis and I want to find out if people who live in California might behave differently if I provide them an offer than people that live in Massachusetts, it's not intuitive to say, oh yeah, that's in customer_seg_ so what data catalogs are doing is they're thinking about that marketing manager, they're thinking about that peer business user and helping make that translation between business terminology, "Hey I want to run some customer segmentation analysis for the West" with the technical, physical model, that underlies the data in that data base which is customer_seg_257 is the table you need to access to get the answer to that question. So as organizations start to adapt more self- service analytics, it's important that we're managing not just the data itself and this translation from technical metadata to business metadata, but there's another layer that's becoming even more important as organizations embrace self- service analytics. And that's how is this data actually being processed? What is the logic that is being used to traverse different data sets that end users now have access to. So if I take gender information in one table and I have information on income on another table, and I have some private information that identifies those two customers as the same in those two tables, in some use tables I can join that data, if I'm doing marketing campaigns, I likely can join that data. >> Sure. >> If I'm running a loan approval process here in the United States, I cannot join that data. >> That's a legal limitation, that's not a technical issue-- >> That's a legal, federal, government issue. Right? And so here's where there's a discussion, in folks that are knowledgeable about data and data management, there's a discussion of how do we govern this data? But I think by saying how we govern this data, we're kind of covering up what's actually going on, because you don't have govern that data so much as you have to govern the analysis. How is this joined, how are we combining these two data sets? If I just govern the data for accuracy, I might not know the usage scenario which is someone wants to combine these two things which makes it's illegal. Separately, it's fine, combined, it's illegal. So now we need to think about, how do we govern the analytics themselves, the logic that is being used. And that gets kind of complicated, right? For a marketing manager to understand the difference between those things on the surface is doesn't really make sense. It only makes sense when the context of that government regulation is shared and explained and in the course of your workflow and dragging and dropping in a Tableau report, you might not remember that, right? >> That's right, and the derivative output that you create that other people might then be able to use because it's back in the data catalog, doesn't explicitly note, often, that this data was generated as a combination of a join that might not be in compliance with any number of different rules. >> Right, so about a year and a half ago, we introduced a new feature in our data catalog called Trust Check. >> Yeah, I really like this. This is a really interesting thing. >> And that was meant to be a way where we could alert end users to these issues- hey, you're trying to run the same analytic and that's not allowed. We're going to give you a warning, we're not going to let you run that query, we're going to stop you in your place. So that was a way in the workflow of someone while they're typing a SQL statement or while they're dragging and dropping in Tableau to surface that up. Now, some of the vendors we work with, like Tableau, have doubled down on this concept of how do they integrate with an enterprise data catalog to make this even easier. So at Tableau conference last week, they introduced a new metadata API, they introduced a Tableau catalog, and the opportunity for these type of alerts to be pushed into the Tableau catalog as well as directly into reports and worksheets and dashboards that end users are using. >> Let me make sure I got this. So it means that you can put a lot of the compliance rules inside Alation and have a metadata API so that Alation effectively is governing the utilization of data inside the Tableau catalog. >> That's right. So think about the integration with Tableau is this communication mechanism to surface up these policies that are stored centrally in your data catalog. And so this is important, this notion of a central place of reference. We used to talk about data catalogs just as a central place of reference for where all your data assets lie in the organizations, and we have some automated ways to crawl those sources and create a centralized inventory. What we've added in our new release, which is coming out here shortly, is the ability to centralize all your policies in that catalog as well as the pointers to your data in that catalog. So you have a single source of reference for how this data needs to be governed, as well as a single source of reference for how this data is used in the organization. >> So does that mean, ultimately, that someone could try to do something, trust check and say, no you can't, but this new capability will say, and here's why or here's what you do. >> Exactly. >> A descriptive step that says let me explain why you can't do it. >> That's right. Let me not just stop your query and tell you no, let me give you the details as to why this query isn't a good query and what you might be able to do to modify that query should you still want to run it. And so all of that context is available for any end user to be able to become more aware of what is the system doing, and why is recommending. And on the flip side, in the world before we had something like Trust Check, the only opportunity for an IT Team to stop those queries was just to stop them without explanation or to try to publish manuals and ask people to run tests, like the DMV, so that they memorized all those rules of governance. >> Yeah, self- service, but if there's a problem you have to call us. >> That's right. That's right. So what we're trying to do is trying to make the work of those governance teams, those IT Teams, much easier by scaling them. Because we all know the volume of data that's being created, the volume of analysis that's being created is far greater than any individual can come up with, so we're trying to scale those precious data expert resources-- >> Digitize them-- >> Yeah, exactly. >> It's a digital transformation of how we acquire data necessary-- >> And then-- >> for data transformation. >> make it super transparent for the end user as to why they're being told yes or no so that we remove this friction that's existed between business and IT when trying to perform analytics. >> But I want to build a little bit on one of the things I thought I heard you say, and that is that the idea that this new feature, this new capability will actually prescribe an alternative, logical way for you to get your information that might be in compliance. Have I got that right? >> Yeah, that's right. Because what we also have in the catalog is a workflow that allows individuals called Stewards, analytics Stewards to be able to make recommendations and certifications. So if there's a policy that says though shall not use the data in this way, the Stewards can then say, but here's an alternative mechanism, here's an alternative method, and by the way, not only are we making this as a recommendation but this is certified for success. We know that our best analysts have already tried this out, or we know that this complies with government regulation. And so this is a more active way, then, for the two parties to collaborate together in a distributed way, that's asynchronous, and so it's easy for everyone no matter what hour of the day they're working or where they're globally located. And it helps progress analytics throughout the organization. >> Oh and more importantly, it increases the likelihood that someone who is told you now have self- service capability doesn't find themselves abandoning it the first time that somebody says no, because we've seen that over and over with a lot of these query tools, right? That somebody says, oh wow, look at this new capability until the screen, you know, metaphorically, goes dark. >> Right, until it becomes too complicated-- >> That's right-- >> and then you're like, oh I guess I wasn't really trained on this. >> And then they walk away. And it doesn't get adopted. >> Right. >> And this is a way, it's very human centered way to bring that self- service analyst into the system and be a full participant in how you generate value out of it. >> And help them along. So you know, the ultimate goal that we have as an organization, is help organizations become our customers, become data literate populations. And you can only become data literate if you get comfortable working with the date and it's not a black box to you. So the more transparency that we can create through our policy center, through documenting the data for end users, and making it more easy for them to access, the better. And so, in the next version of the Alation product, not only have we implemented features for analytic Stewards to use, to certify these different assets, to log their policies, to ensure that they can document those policies fully with examples and use cases, but we're also bringing to market a professional services offering from our own team that says look, given that we've now worked with about 20% of our installed base, and observed how they roll out Stewardship initiatives and how they assign Stewards and how they manage this process, and how they manage incentives, we've done a lot of thinking about what are some of the best practices for having a strong analytics Stewardship practice if you're a self- service analytics oriented organization. And so our professional services team is now available to help organizations roll out this type of initiative, make it successful, and have that be supported with product. So the psychological incentives of how you get one of these programs really healthy is important. >> Look, you guys have always been very focused on ensuring that your customers were able to adopt valued proposition, not just buy the valued proposition. >> Right. >> Stephanie McReynolds, Senior Vice President of Marketing Relation, once again, thanks for being on theCUBE. >> Thanks for having me. >> And thank you for joining us for another CUBE conversation. I'm Peter Burris. See you next time.

(techno music) >> From Cambridge, Massachusetts, it's theCUBE. Covering MIT Chief Data Officer and Information Quality Symposium 2019, brought to you by SiliconANGLE Media. >> Welcome back to MIT CDOIQ. The CDO Information Quality Conference. You're watching theCUBE, the leader in live tech coverage. My name is Dave Vellante. I'm here with my co-host, Paul Gillin. This is our day two of our two day coverage. Jean Ross is here. She's the principle research scientist at MIT CISR, Jean good to see you again. >> Nice to be here! >> Welcome back. Okay, what do all these acronyms stand for, I forget. MIT CISR. >> CISR which we pronounce scissor, is the Center for Information Systems Research. It's a research center that's been at MIT since 1974, studying how big companies use technology effectively. >> So and, what's your role as a research scientist? >> As a research scientist, I work with both researchers and with company leaders to understand what's going on out there, and try to present some simple succinct ideas about how companies can generate greater value from information technology. >> Well, I guess not much has changed in information technology since 1974. (laughing) So let's fast forward to the big, hot trend, digital transformation, digital business. What's the difference between a business and a digital business? >> Right now, you're hoping there's no difference for you and your business. >> (chuckling) Yeah, for sure. >> The main thing about a digital business is it's being inspired by technology. So in the past, we would establish a strategy, and then we would check out technology and say, okay, how can technology make us more effective with that strategy? Today, and this has been driven a lot by start-ups, we have to stop and say, well wait a minute, what is technology making possible? Because if we're not thinking about it, there sure are a lot of students at MIT who are, and we're going to miss the boat. We're going to get Ubered if you will, somebody's going to think of a value proposition that we should be offering and aren't, and we'll be left in the dust. So, our digital businesses are those that are recognizing the opportunities that digital technologies make possible. >> Now, and what about data? In terms of the role of digital business, it seems like that's an underpinning of a digital business. Is it not? >> Yeah, the single biggest capability that digital technologies provide, is ubiquitous data that's readily accessible anytime. So when we think about being inspired by technology, we could reframe that as inspired by the availability of ubiquitous data that's readily accessible. >> Your premise about the difference between digitization and digital business is interesting. It's more than just a sematic debate. Do companies now, when companies talk about digital transformation these days, in fact, are most of them of thinking of digitization rather than really transformative business change? >> Yeah, this is so interesting to me. In 2006, we wrote a book that said, you need to become more agile, and you need to rely on information technology to get you there. And these are basic things like SAP and salesforce.com and things like that. Just making sure that your core processes are disciplined and reliable and predictable. We said this in 2006. What we didn't know is that we were explaining digitization, which is very effective use of technology in your underlying process. Today, when somebody says to me, we're going digital, I'm thinking about the new value propositions, the implications of the data, right? And they're often actually saying they're finally doing what we thought they should do in 2006. The problem is, in 2006, we said get going on this, it's a long journey. This could take you six, 10 years to accomplish. And then we gave examples of companies that took six to 10 years. LEGO, and USAA and really great companies. And now, companies are going, "Ah, you know, we really ought to do that". They don't have six to 10 years. They get this done now, or they're in trouble, and it's still a really big deal. >> So how realistic is it? I mean, you've got big established companies that have got all these information silos, as we've been hearing for the last two days, just pulling their information together, knowing what they've got is a huge challenge for them. Meanwhile, you're competing with born on the web, digitally native start-ups that don't have any of that legacy, is it really feasible for these companies to reinvent themselves in the way you're talking about? Or should they just be buying the companies that have already done it? >> Well good luck with buying, because what happens is that when a company starts up, they can do anything, but they can't do it to scale. So most of these start-ups are going to have to sell themselves because they don't know anything about scale. And the problem is, the companies that want to buy them up know about the scale of big global companies but they don't know how to do this seamlessly because they didn't do the basic digitization. They relied on basically, a lot of heroes in their company to pull of the scale. So now they have to rely more on technology than they did in the past, but they still have a leg up if you will, on the start-up that doesn't want to worry about the discipline of scaling up a good idea. They'd rather just go off and have another good idea, right? They're perpetual entrepreneurs if you will. So if we look at the start-ups, they're not really your concern. Your concern is the very well run company, that's been around, knows how to be inspired by technology and now says, "Oh I see what you're capable of doing, "or should be capable of doing. "I think I'll move into your space". So this, the Amazon's, and the USAA's and the LEGO's who say "We're good at what we do, "and we could be doing more". We're watching Schneider Electric, Phillips's, Ferovial. These are big ole companies who get digital, and they are going to start moving into a lot of people's territory. >> So let's take the example of those incumbents that you've used as examples of companies that are leaning into digital, and presumably doing a good job of it, they've got a lot of legacy debt, as you know people call it technical debt. The question I have is how they're using machine intelligence. So if you think about Facebook, Amazon, Microsoft, Google, they own horizontal technologies around machine intelligence. The incumbents that you mentioned, do not. Now do they close the gap? They're not going to build their own A.I. They're going to buy it, and then apply it. It's how they apply it that's going to be the difference. So do you agree with that premise, and where are they getting it, do they have the skill sets to do it, how are they closing that gap? >> They're definitely partnering. When you say they're not going to build any of it, that's actually not quite true. They're going to build a lot around the edges. They'll rely on partners like Microsoft and Google to provide some of the core, >> Yes, right. >> But they are bringing in their own experts to take it to the, basically to the customer level. How do I take, let me just take Schneider Electric for an example. They have gone from being an electrical equipment manufacturer, to a purveyor of energy management solutions. It's quite a different value proposition. To do that, they need a lot of intelligence. Some of it is data analytics of old, and some of it is just better representation on dashboards and things like that. But there is a layer of intelligence that is new, and it is absolutely essential to them by relying on partners and their own expertise in what they do for customers, and then co-creating a fair amount with customers, they can do things that other companies cannot. >> And they're developing a software presumably, a SAS revenue stream as part of that, right? >> Yeah, absolutely. >> How about the innovators dilemma though, the problem that these companies often have grown up, they're very big, they're very profitable, they see disruption coming, but they are unable to make the change, their shareholders won't let them make the change, they know what they have to do, but they're simply not able to do it, and then they become paralyzed. Is there a -- I mean, looking at some of the companies you just mentioned, how did they get over that mindset? >> This is real leadership from CEO's, who basically explain to their boards and to their investors, this is our future, we are... we're either going this direction or we're going down. And they sell it. It's brilliant salesmanship, and it's why when we go out to study great companies, we don't have that many to choose from. I mean, they are hard to find, right? So you are at such a competitive advantage right now. If you understand, if your own internal processes are cleaned up and you know how to rely on the E.R.P's and the C.R.M's, to get that done, and on the other hand, you're using the intelligence to provide value propositions, that new technologies and data make possible, that is an incredibly powerful combination, but you have to invest. You have to convince your boards and your investors that it's a good idea, you have to change your talent internally, and the biggest surprise is, you have to convince your customers that they want something from you that they never wanted before. So you got a lot of work to do to pull this off. >> Right now, in today's economy, the economy is sort of lifting all boats. But as we saw when the .com implosion happened in 2001, often these breakdown gives birth to great, new companies. Do you see that the next recession, which is inevitably coming, will be sort of the turning point for some of these companies that can't change? >> It's a really good question. I do expect that there are going to be companies that don't make it. And I think that they will fail at different rates based on their, not just the economy, but their industry, and what competitors do, and things like that. But I do think we're going to see some companies fail. We're going to see many other companies understand that they are too complex. They are simply too complex. They cannot do things end to end and seamlessly and present a great customer experience, because they're doing everything. So we're going to see some pretty dramatic changes, we're going to see failure, it's a fair assumption that when we see the economy crash, it's also going to contribute, but that's, it's not the whole story. >> But when the .com blew up, you had the internet guys that actually had a business model to make money, and the guys that didn't, the guys that didn't went away, and then you also had the incumbents that embrace the internet, so when we came out of that .com downturn, you had the survivors, who was Google and eBay, and obviously Amazon, and then you had incumbent companies who had online retailing, and e-tailing and e-commerce etc, who thrived. I would suspect you're going to see something similar, but I wonder what you guys think. The street today is rewarding growth. And we got another near record high today after the rate cut yesterday. And so, but companies that aren't making money are getting rewarded, 'cause they're growing. Well when the recession comes, those guys are going to get crushed. >> Right. >> Yeah. >> And you're going to have these other companies emerge, and you'll see the winners, are going to be those ones who have truly digitized, not just talking the talk, or transformed really, to use your definition. That's what I would expect. I don't know, what do you think about that? >> I totally agree. And, I mean, we look at industries like retail, and they have been fundamentally transformed. There's still lots of opportunities for innovation, and we're going to see some winners that have kind of struggled early but not given up, and they're kind of finding their footing. But we're losing some. We're losing a lot, right? I think the surprise is that we thought digital was going to replace what we did. We'd stop going to stores, we'd stop reading books, we wouldn't have newspapers anymore. And it hasn't done that. Its only added, it hasn't taken anything away. >> It could-- >> I don't think the newspaper industry has been unscathed by digital. >> No, nor has retail. >> Nor has retail, right. >> No, no no, not unscathed, but here's the big challenge. Is if I could substitute, If I could move from newspaper to online, I'm fine. You don't get to do that. You add online to what you've got, right? And I think this right now is the big challenge. Is that nothing's gone away, at least yet. So we have to sustain the business we are, so that it can feed the business we want to be. And we have to make that transition into new capabilities. I would argue that established companies need to become very binary, that there are people that do nothing but sustain and make better and better and better, who they are. While others, are creating the new reality. You see this in auto companies by the way. They're creating not just the autonomous automobiles, but the mobility services, the whole new value propositions, that will become a bigger and bigger part of their revenue stream, but right now are tiny. >> So, here's the scary thing to me. And again, I'd love to hear your thoughts on this. And I've been an outspoken critic of Liz Warren's attack on big tech. >> Absolutely. >> I just think if they're breaking the law, and they're really acting like monopolies, the D.O.J and F.T.C should do something, but to me, you don't just break up big tech because they're good capitalists. Having said that, one of the things that scares me is, when you see Apple getting into payment systems, Amazon getting into grocery and logistics. Digital allows you to do something that's never happened before which is, you can traverse industries. >> Yep. >> Yeah, absolutely >> You used to have this stack of industries, and if you were in that industry, you're stuck in healthcare, you're stuck in financial services or whatever it was. And today, digital allows you to traverse those. >> It absolutely does. And so in theory, Amazon and Apple and Facebook and Google, they can attack virtually any industry and they kind of are. >> Yeah they kind are. I would certainly not break up anything. I would really look hard though at acquisitions, because I think that's where some of this is coming from. They can stop the overwhelming growth, but I do think you're right. That you get these opportunities from digital that are just so much easier because they're basically sharing information and technology, not building buildings and equipment and all that kind of thing. But I think there all limits to all this. I do not fear these companies. I think there, we need some law, we need some regulations, they're fine. They are adding a lot of value and the great companies, I mean, you look at the Schneider's and the Phillips, yeah they fear what some of them can do, but they're looking forward to what they provide underneath. >> Doesn't Cloud change the equation here? I mean, when you think of something like Amazon getting into the payments business, or Google in the payments business, you know it used to be that the creating of global payments processing network, just going global was a huge barrier to entry. Now, you don't have nearly that same level of impediment right? I mean the cloud eliminates much of the traditional barrier. >> Yeah, but I'll tell you what limits it, is complexity. Every company we've studied gets a little over anxious and becomes too complex, and they cannot run themselves effectively anymore. It happens to everyone. I mean, remember when we were terrified about what Microsoft was going to become? But then it got competition because it's trying to do so many things, and somebody else is offering, Sales Force and others, something simpler. And this will happen to every company that gets overly ambitious. Something simpler will come along, and everybody will go "Oh thank goodness". Something simpler. >> Well with Microsoft, I would argue two things. One is the D.O.J put some handcuffs on them , and two, with Steve Ballmer, I wouldn't get his nose out of Windows, and then finally stuck on a (mumbles) (laughter) >> Well it's they had a platform shift. >> Well this is exactly it. They will make those kind of calls . >> Sure, and I think that talks to their legacy, that they won't end up like Digital Equipment Corp or Wang and D.G, who just ignored the future and held onto the past. But I think, a colleague of ours, David Moschella wrote a book, it's called "Seeing Digital". And his premise was we're moving from a world of remote cloud services, to one where you have to, to use your word, ubiquitous digital services that you can access upon which you can build your business and new business models. I mean, the simplest example is Waves, you mentioned Uber. They're using Cloud, they're using OAuth.in with Google, Facebook or LinkedIn and they've got a security layer, there's an A.I layer, there's all your BlockChain, mobile, cognitive, it's all these sets of services that are now ubiquitous on which you're building, so you're leveraging, he calls it the matrix, to the extent that these companies that you're studying, these incumbents can leverage that matrix, they should be fine. >> Yes. >> The part of the problem is, they say "No, we're going to invent everything ourselves, we're going to build it all ourselves". To use Andy Jassy's term, it's non-differentiated heavy lifting, slows them down, but there's no reason why they can't tap that matrix, >> Absolutely >> And take advantage of it. Where I do get scared is, the Facebooks, Apples, Googles, Amazons, they're matrix companies, their data is at their core, and they get this. It's not like they're putting data around the core, data is the core. So your thoughts on that? I mean, it looks like your slide about disruption, it's coming. >> Yeah, yeah, yeah, yeah. >> No industry is safe. >> Yeah, well I'll go back to the complexity argument. We studied complexity at length, and complexity is a killer. And as we get too ambitious, and we're constantly looking for growth, we start doing things that create more and more tensions in our various lines of business, causes to create silos, that then we have to coordinate. I just think every single company that, no cloud is going to save us from this. It, complexity will kill us. And we have to keep reminding ourselves to limit that complexity, and we've just not seen the example of the company that got that right. Sooner or later, they just kind of chop them, you know, create problems for themselves. >> Well isn't that inherent though in growth? >> Absolutely! >> It's just like, big companies slow down. >> That's right. >> They can't make decisions as quickly. >> That's right. >> I haven't seen a big company yet that moves nimbly. >> Exactly, and that's the complexity thing-- >> Well wait a minute, what about AWS? They're a 40 billion dollar company. >> Oh yeah, yeah, yeah >> They're like the agile gorilla. >> Yeah, yeah, yeah. >> I mean, I think they're breaking the rule, and my argument would be, because they have data at their core, and they've got that, its a bromide, but that common data model, that they can apply now to virtually any business. You know, we're been expecting, a lot of people have been expecting that growth to attenuate. I mean it hasn't yet, we'll see. But they're like a 40 billion dollar firm-- >> No that's a good example yeah. >> So we'll see. And Microsoft, is the other one. Microsoft is demonstrating double digit growth. For such a large company, it's astounding. I wonder, if the law of large numbers is being challenged, so. >> Yeah, well it's interesting. I do think that what now constitutes "so big" that you're really going to struggle with the complexity. I think that has definitely been elevated a lot. But I still think there will be a point at which human beings can't handle-- >> They're getting away. >> Whatever level of complexity we reach, yeah. >> Well sure, right because even though this great new, it's your point. Cloud technology, you know, there's going to be something better that comes along. Even, I think Jassy might have said, If we had to do it all over again, we would have built the whole thing on lambda functions >> Yeah. >> Oh, yeah. >> Not on, you know so there you go. >> So maybe someone else does that-- >> Yeah, there you go. >> So now they've got their hybrid. >> Yeah, yeah. >> Yeah, absolutely. >> You know maybe it'll take another ten years, but well Jean, thanks so much for coming to theCUBE, >> it was great to have you. >> My pleasure! >> Appreciate you coming back. >> Really fun to talk. >> All right, keep right there everybody, Paul Gillin and Dave Villante, we'll be right back from MIT CDOIQ, you're watching theCUBE. (chuckles) (techno music)

>> Live, from Las Vegas, it's theCUBE, covering Magento Imagine 2019, brought to you Adobe. >> Welcome back to theCUBE, Lisa Martin with Jeff Frick. We have been covering Imagine 2019 in Vegas, all day today, talking all things eCommerce, innovation, technology, the customer experience. Jeff, one of the biggest themes, I think, that we've heard today, from all of our guests, is how strong this community is, how naturally it was developed in the last ten years, and how influential it is to delivering exceptional customer experience technology. >> In fact, Jason said without the community, there would be no Magento. So it's, it's ingrained in the culture. It's ingrained in the DNA. I think, you know, doing some of the research, you know, there was people talking about the dark days of Magento, as it went into eBay, and apparently whatever that plan was, that didn't work. And then out of eBay into private equity. Out of private equity into, now, Adobe. And it sounds like the community's kind of been following along, and maybe they were holding their breath a little bit, a year ago, but it sounds like they kind of got through that, that kind of concern knothole, if you will, and kind of popped out the other side, and realized there's a whole lot of opportunity that comes to Magento, via being part of Adobe now that they didn't have before. So I think, it sounds like they're good with it, and they're ready to go, and nothing but opportunity ahead. >> Yeah, you know, I think with any acquisition, and, you know, we cover so many technology shows, and we've been part of acquisitions before at different companies. They're challenging. There's always, I think, natural trepidation. I think it's just a natural response that anybody, probably, from an executive to an individual contributor level, is going to have. But one of the things that came up so resolutely, was how organic the Magento community has been developed over time. That, like you said, as Jason was saying, without it, there is no Magento. Not only are they influential. It's very much a symbiotic relationship, that pleasantly, surprisingly, sounds like it's been integrated very nicely, into Adobe. And to your point, they now are seeing, wow, there's a tremendous amount of technology and resources that we didn't have the opportunity to leverage before. Talking about the experience, the digital experience business of Adobe's, which is growing. Grew 20% year over year, 2017 to 2018. On a very strong trajectory this year. A lot of opportunity to enable merchants of any size to have this really 360 degree of the customer experience, and manage it with analytics, and advertising, and marketing, and add the commerce piece, so that they can take that marketing interaction and actually convert it to revenue. >> Right, right. I mean, look at Adobe. I mean, they brought in Magento, which we know, late last year. They also brought in Marketo at almost about the same time, $4.7 billion. So they're making huge moves. And I think it's a pretty unique situation, where, again, they come from the creative, and now, with the data, and a sophisticated platform, and you talk about the AB testing, again. It used to be just AB, now it's AB times literally millions and millions of customized experiences delivered to the client. And then now, again, I think really an interesting point of view is where then you bring the commerce to the point of engagement rather than trying to use the engagement as a way to drive people to commerce. I mean, they seem really well positioned, I think they're going to really enjoy people like Accenture, and some of the of the other big system integrators that now are going to be, you know, behind this platform. So it seems to be a fit, a marriage made in heaven. It almost makes you wonder why Adobe was so late to have an eCommerce platform, which is the thing that kind of surprises me, I think, the most. >> Yeah, well, it also gives them the opportunity to compete with Shopify and with Salesforce Commerce, and kind of harness this brand power. But you talked about something that we've talked about all day, and that's bringing the transaction and the commerce experience to me as a consumer wherever I am, whether it's in app shopping through Instagram. Rather than, you know, delivering me a personalized experience, leveraging the power of these technologies, to understand the right things about me as a consumer, to deliver me an experience that is frictionless. It's going to allow me to have a seamless experience. We talked about that with progressive web apps, and how that's going to enable next generation shopping for merchants of all sizes to enable. Don't just engage me on my mobile, if that's where I want to be. If you don't have the opportunity to convert me seamlessly to actually transact, there's a huge adjustable market or gap in converting that to revenue, which Jason Woolsey also talked about. Kind of thinking about next steps for Adobe and what they're going to be able to do to help those merchants capture in real time, leveraging the power of technology, emerging technologies like AI, in real-time to make that shoppable moment turn into dollars for the merchant. >> Right, lot of great things. I thought it was interesting having TJ Gamble on, and talked about coopetition. Right? Coopetition is such a fundamental part of Silicon Valley and the world in which we live in. And he said, you know, if you're making fat margin, as Jeff Bezos loves to say, your margin is my opportunity. You're going to compete with Amazon, but in the meantime, you got to compete with them. So to enable integration into the Amazon platform with your Magento store, the integration into Google Shopping, integration into Instagram purchases, in app purchases, I mean, these really opening up the opportunities for these smaller retailers, mid-sized retailers, to compete in a really complicated and super hyper-competitive world. But now they can, again, focus on their brand, which we hear over and over and over, focus on their experience, focus on their community, and leverage some of this special breed technology under the covers across platform, across different modes of buying. Because the other thing we hear over and over and over is you got to give people choice. You can't say no. So if they want to buy it through Amazon, let 'em buy it through Amazon. If they want to buy it through Instagram, let 'em buy it through Instagram. If they want to come to you eCommerce site, let 'em come to your eCommerce site But, you know, in opening up all those channels for the merchant to be able to execute their transactions regardless of how the customer got to them, or how, more importantly, they got to the customer. >> And, you know, the SMB front is really key that you brought up, because, in the last year, since the acquisition was announced, about a year ago, and completed, I think in September of 2018, there was not just concern from the community, that we talked about at the beginning of this segment, but also the small and the medium business. Like, well, Adobe has a really big presence in enterprise. Is that going to be cannibalized with this acquisition of Magento, who had such a strong presence with those smaller merchants? And you mentioned some of thee things with Amazon and Google that we heard yesterday and today. I think really assuaging some of those concerns that the smaller businesses had, but also, allowing these smaller merchants to sort of level the playing field, and have access to the power of a branded Amazon storefront that allows a smaller business to get some differentiation, whereas before they didn't have that. So I think we heard a lot about that today, and how, I think, those smaller brands are probably, maybe breathing a sign of relief, that this acquisition is really going to enable them, with a lot more tools, but not at the, you know, cannibalizing what they have been doing with Magento for so long. >> Right, right. And some other fun discussions. I really enjoyed the time with Tina, talking about influencer marketing. It's amazing how that continues to evolve at a really fast pace. Right? A derivation of professional endorsement, which is something we've known ever since Joe Namath put on stockings many moons ago. But to see it go from big influencers, to micro-influencers, you know. How do you sponsor people, give them money, engage as a brand, and still maintain that they legitimately like your product, use your product. I think it's a really fascinating space to, again, to be able to purchase within that Instagram application, I think, is really interesting. And then a lot of conversations about the post transaction engagement. You know, send them not one email confirmation that your items are coming, but send them two. And really to think about lifetime value of the customer, and engaging the customer via content, and, oh, by the way, there'll be some transactions in commerce as well. I think it's really forward-looking, and really enjoyed that conversation as well. >> I did too. I didn't know the difference between an influencer and a micro-influencer, and you kind of infer based on just the name alone. But also how brands have the opportunity to leverage data, to evaluate maybe we should actually make more investments in somebody with a thousand followers, for example, than somebody with a hundred thousand. Because the revenue attribution, or the website traffic lift that they're going to get from a micro-influencer could far outweigh the benefits, financially, than going with somebody, a celebrity or what not, that, as you said, back to, you know, Joe Namath, many decades ago. So that was interesting, but it's also a good use of using data to build brand reputation, build, increase customer lifetime value, but also get so much more targeted, and really understand how to operationalize the commerce portion of your business, and through whom, through which channels you're going to see the biggest bang for your buck. >> Yeah, it's really interesting times, you know, this idea that the apps follow you. I mean, my favorite example is Spotify. Super sophisticated app. Right? I can be listening to my phone. I get into my car. It follows me. I go into my office. It follows me on my computer. I go out on my bike. It follows me. It stays the same state. And so, for the commerce and the community to be able to follow you around is a really interesting idea. And again, it was Hillary Mason, actually, that first came up with the term that, you know, AI, and good recommendations done well are magic, and done poorly, are creepy. I think it's always going to be this interesting fine line. Again, I think the whole concept of, you know, using old data and how fast do you update it, and that's kind of the example. I've been looking at tents. I bought a tent. I don't want to see ads for tents anymore. Right? It's time to see an ad for a sleeping bag, or a camp stove. And these are really happening in real-time. You know, we've heard about Omnichannel. We've heard about 360 view of the customer, ad nauseam. You've been in this business for a long time. But it sounds like it's finally coming together, and it's finally where we have the data, we have the access to the data, the speed of the analytics, and just the raw horsepower in modeling that we can now start to apply this real-time, ML, to data, in-flight, to be able to serve up the not creepy but correct recommendations, at the right time to the right person. It's getting closer and closer to reality. >> It is getting closer, and as you were talking about that, one of the things that popped into my head is going from the creepy to the magic that is, you think, wow, is really leveraging this data and using the power of machine learning and AI, a great facilitator. Or is the bottom foundation order management? If you don't have the, or inventory management. If you don't have the inventory, it's great to have all these capabilities to transact in real time, but if you can't fulfill it, you're going to sink. >> Yeah. >> So Magento, with, you know, some of their core technology enabling this. Really enabling, not just enabling the 360 degree customer view, but being able to fulfill it. Those are table stakes, and game changers. >> Right. >> For merchants of any size. >> Right, and I think they do have to engage. I mean, they have to be brands. Right? Because a commodity item I can go get anywhere. There's got to be a reason to come. Lot of conversations, not so much here, but at the Adobe summit, in terms of the content piece, and having an ongoing dialog and an ongoing content relationship, with your client. Now you can slice and dice and serve that up lots of different ways based on who they are and the context. But if you don't have that, you can't just compete on price. You just can't compete on inventory, 'cause Amazon is going to win. Right? You can't stock, my favorite thing is, is shirt, shirt little pins in here. How do you stock those? You can't. They don't cost any money, and you don't sell that many. Amazon can. So, find you niche, you know. Engage your customers. Engage your community, and there'll be some transactions that come along with this. And I think it's really reinforced that, I think, its probably really timely for Magento to be part of Adobe, because eCommerce, just purely by itself, is going to be tougher and tougher to do unless you've got this deeper relationship with your customers, beyond simply transacting something. >> Exactly. So I enjoyed hosting, as I always do with you, Jeff. Learned a lot today, and excited to hear about what's next for this event, now that Adobe is leveraging the power of Magento. >> Well, we heard the announcements, Gary's going to make the announcement tomorrow. So hang out for the keynote tomorrow to find out more about Imagine 2020. We'll be there. >> 2020, yes. >> 2020, because we'll know everything in 2020. >> We will know. That's right. I can't wait. >> 2020 hindsight. >> I'm waiting for that. Well, Jeff, as I said, always a pleasure hosting with you. >> You too, Lisa. >> I brought the sea urchin necklace out. >> I like it. I like it. >> This is just for Jeff. It's making it's appearance on theCUBE. We want to thank you for watching, for Jeff Frick, I'm Lisa Martin, and you've been watching theCUBE live from Imagine 19 at The Wynn Las Vegas. Thanks for watching. (upbeat music)