>> Voice Over: Data is at the heart of transformation, and the change every company needs to succeed. But it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions, all at the speed of digital. The transformation starts with you, it's time to lead the way, it's time for thought leaders. (soft upbeat music) >> Welcome to Thought.Leaders a digital event brought to you by ThoughtSpot, my name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers, and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not, ThoughtSpot is disrupting analytics, by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core, requires not only modern technology but leadership, a mindset and a culture, that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action? And today we're going to hear from experienced leaders who are transforming their organizations with data, insights, and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot. First, chief data strategy officer of the ThoughtSpot is Cindi Howson, Cindi is an analytics and BI expert with 20 plus years experience, and the author of Successful Business Intelligence: Unlock the Value of BI & Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics Magic Quadrant. In early last year, she joined ThoughtSpot to help CEOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi great to see you, welcome to the show. >> Thank you Dave, nice to join you virtually. >> Now our second cohost and friend of theCUBE is ThoughtSpot CEO Sudheesh Nair Hello Sudheesh, how are you doing today? >> I'm well, good to talk to you again. >> That's great to see you, thanks so much for being here. Now Sudheesh, please share with us why this discussion is so important to your customers and of course to our audience, and what they're going to learn today. (upbeat music) >> Thanks Dave, I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Look, since we have all been you know, cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with, invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one, that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time, we want to make sure that we value your time, then this is going to be used. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people, that you want to hang around with long after this event is over. And number three, as we plan through this, you know we are living through these difficult times we want this event to be more of an uplifting and inspiring event too. Now, the challenge is how do you do that with the team being change agents, because teens and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do or likes to do. The way I think of it, changes sort of like, if you've ever done bungee jumping, and it's like standing on the edges, waiting to make that one more step you know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step today. Change requires a lot of courage, and when we are talking about data and analytics, which is already like such a hard topic not necessarily an uplifting and positive conversation most businesses, it is somewhat scary, change becomes all the more difficult. Ultimately change requires courage, courage to first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that you know, maybe I don't have the power to make the change that the company needs, sometimes they feel like I don't have the skills, sometimes they may feel that I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations when it comes to data and insights that you talked about. You know, that are people in the company who are going to have the data because they know how to manage the data, how to inquire and extract, they know how to speak data, they have the skills to do that. But they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is the silo of people with the answers, and there is a silo of people with the questions, and there is gap, this sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force sometimes. It could be a tool, it could be a platform, it could be a person, it could be a process but sometimes no matter how big the company is or how small the company is you may need to bring some external stimuli to start the domino of the positive changes that are necessary. The group of people that we are brought in, the four people, including Cindi that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to dress the rope, that you will be safe and you're going to have fun, you will have that exhilarating feeling of jumping for a bungee jump, all four of them are exceptional, but my owner is to introduce Michelle. And she's our first speaker, Michelle I am very happy after watching our presentation and reading your bio that there are no country vital worldwide competition for cool parents, because she will beat all of us. Because when her children were small, they were probably into Harry Potter and Disney and she was managing a business and leading change there. And then as her kids grew up and got to that age where they like football and NFL, guess what? She's the CIO of NFL, what a cool mom. I am extremely excited to see what she's going to talk about. I've seen this slides, a bunch of amazing pictures, I'm looking to see the context behind it, I'm very thrilled to make that client so far, Michelle, I'm looking forward to her talk next. Welcome Michelle, it's over to you. (soft upbeat music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one, and I thought this is about as close as I'm ever going to get. So I want to talk to you about quarterbacking our digital revolution using insights data, and of course as you said, leadership. First a little bit about myself, a little background as I said, I always wanted to play football, and this is something that I wanted to do since I was a child, but when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines, and a female official on the field. I'm a lifelong fan and student of the game of football, I grew up in the South, you can tell from the accent and in the South is like a religion and you pick sides. I chose Auburn University working in the Athletic Department, so I'm testament to you can start the journey can be long it took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well, not actually not so little, he played offensive line for the Alabama Crimson Tide. And for those of you who know SEC football you know, this is a really big rivalry. And when you choose sides, your family is divided, so it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL he just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands. Delivering memories and amazing experiences that delight from Universal Studios, Disney to my current position as CIO of the NFL. In this job I'm very privileged to have the opportunity to work with the team, that gets to bring America's game to millions of people around the world. Often I'm asked to talk about how to create amazing experiences for fans, guests, or customers. But today I really wanted to focus on something different and talk to you about being behind the scenes and backstage. Because behind every event every game, every awesome moment is execution, precise repeatable execution. And most of my career has been behind the scenes, doing just that, assembling teams to execute these plans, and the key way that companies operate at these exceptional levels, is making good decisions, the right decisions at the right time and based upon data, so that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves. And it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kinds of world-class experiences are often seeking out and leveraging next generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute. A little bit first about Disney, in the 90s I was at Disney, leading a project called destination Disney, which it's a data project, it was a data project, but it was CRM before CRM was even cool. And then certainly before anything like a data-driven culture was ever brought up. But way back then we were creating a digital backbone that enabled many technologies for the things that you see today, like the magic band, just these magical express. My career at Disney began in finance, but Disney was very good about rotating you around, and it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team, asking for data more and more data. And I learned that all of that valuable data was locked up in our systems, all of our point of sales systems, our reservation systems, our operation systems, and so I became a shadow IT person in marketing, ultimately leading to moving into IT, and I haven't looked back since. In the early 2000s I was at Universal Studios Theme Park as their CIO, preparing for and launching the wizarding world of Harry Potter. Bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wand selects you at a wine shop. As today at the NFL, I am constantly challenged to do leading edge technologies using things like sensors, AI, machine learning, and all new communication strategies, and using data to drive everything from player performance, contracts to where we build new stadiums and hold events. With this year being the most challenging, yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contract tracing devices joined with testing data. Talk about data, actually enabling your business without it we wouldn't be having a season right now. I'm also on the board of directors of two public companies, where data and collaboration are paramount. First RingCentral, it's a cloud based unified communications platform, and collaboration with video message and phone, all in one solution in the cloud. And Quotient Technologies, whose product is actually data. The tagline at quotient is the result in knowing. I think that's really important, because not all of us are data companies, where your product is actually data. But we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about, as thought leaders in your companies. First just hit on it is change, how to be a champion and a driver of change. Second, how to use data to drive performance for your company, and measure performance of your company. Third, how companies now require intense collaboration to operate, and finally, how much of this is accomplished through solid data-driven decisions. First let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it, and thankfully for the most part knock on wood we were prepared for it. But this year everyone's cheese was moved, all the people in the back rooms, IT, data architects and others, were suddenly called to the forefront. Because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, the 2020 Draft. We went from planning, a large event in Las Vegas under the bright lights red carpet stage to smaller events in club facilities. And then ultimately to one where everyone coaches, GMs, prospects and even our commissioner were at home in their basements. And we only had a few weeks to figure it out. I found myself for the first time being in the live broadcast event space, talking about bungee dress jumping, this is really what it felt like. It was one in which no one felt comfortable, because it had not been done before. But leading through this, I stepped up, but it was very scary, it was certainly very risky but it ended up being Oh, so rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at this level, highest level. As an example, the NFL has always measured performance obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field, you can see points being scored and stats, and you immediately know that impact, those with the best stats, usually win the games. The NFL has always recorded stats, since the beginning of time, here at the NFL a little this year as our 100 and first year and athletes ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us, is both how much more we can measure, and the immediacy with which it can be measured. And I'm sure in your business, it's the same, the amount of data you must have has got to have quadrupled recently and how fast you need it and how quickly you need to analyze it, is so important. And it's very important to break the silos between the keys to the data and the use of the data. Our next generation stats platform is taking data to a next level, it's powered by Amazon Web Services, and we gathered this data real time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast, and of course it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize, route patterns speed, matchups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that we'll gather more and more information about player's performance as it relates to their health and safety. The third trend is really I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes it's important to think about for those of you that are IT professionals and developers, you know more than 10 years ago, agile practices began sweeping companies or small teams would work together rapidly in a very flexible, adaptive and innovative way, and it proved to be transformational. However today, of course, that is no longer just small teams the next big wave of change, and we've seen it through this pandemic is that it's the whole enterprise that must collaborate and be agile. If I look back on my career when I was at Disney, we owned everything 100%, we made a decision, we implemented it, we were a collaborative culture but it was much easier to push change because you own the whole decision. If there was buy in from the top down, you got the people from the bottom up to do it, and you executed. At Universal, we were a joint venture, our attractions and entertainment was licensed, our hotels were owned and managed by other third parties. So influence and collaboration and how to share across companies became very important. And now here I am at the NFL and even the bigger ecosystem. We have 32 clubs that are all separate businesses 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved centralized control has gotten less and less and has been replaced by intense collaboration not only within your own company, but across companies. The ability to work in a collaborative way across businesses and even other companies that has been a big key to my success in my career. I believe this whole vertical integration and big top down decision making is going by the wayside in favor of ecosystems that require cooperation, yet competition to coexist. I mean the NFL is a great example of what we call coopertition, which is cooperation and competition. When in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data-driven decisions and culture. Data on its own isn't good enough, you must be able to turn it to insights, partnerships between technology teams who usually hold the keys to the raw data, and business units who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be, data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask? It's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with first of all making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave, and drive, don't do the ride along program, it's very important to drive, driving can be high risk but it's also high reward. Embracing the uncertainty of what will happen, is how you become brave, get more and more comfortable with uncertainty be calm and let data be your map on your journey, thanks. >> Michelle, thank you so much. So you and I share a love of data, and a love of football. You said you want to be the quarterback, I'm more an old wine person. (Michelle laughing) >> Well, then I can do my job without you. >> Great, and I'm getting the feeling now you know, Sudheesh is talking about bungee jumping. My boat is when we're past this pandemic, we both take them to the Delaware Water Gap and we do the cliff jumping. >> That sounds good, I'll watch. >> You'll watch, okay, so Michelle, you have so many stakeholders when you're trying to prioritize the different voices, you have the players, you have the owners you have the league, as you mentioned to the broadcasters your, your partners here and football mamas like myself. How do you prioritize when there's so many different stakeholders that you need to satisfy? I think balancing across stakeholders starts with aligning on a mission. And if you spend a lot of time understanding where everyone's coming from, and you can find the common thread ties them all together you sort of do get them to naturally prioritize their work, and I think that's very important. So for us at the NFL, and even at Disney, it was our core values and our core purpose is so well known, and when anything challenges that we're able to sort of lay that out. But as a change agent, you have to be very empathetic, and I would say empathy is probably your strongest skill if you're a change agent. And that means listening to every single stakeholder even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic and having a mission and understanding it, is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling. So I thank you for your metership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (soft upbeat music) >> So we're going to take a hard pivot now and go from football to Chernobyl, Chernobyl, what went wrong? 1986, as the reactors were melting down they had the data to say, this is going to be catastrophic and yet the culture said, "No, we're perfect, hide it. Don't dare tell anyone," which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure the additional thousands getting cancer, and 20,000 years before the ground around there and even be inhabited again, This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with, and this is why I want you to focus on having fostering a data-driven culture. I don't want you to be a laggard, I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology, isn't really two sides of the same coin, real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology, and recently a CDO said to me, "You know Cindi, I actually think this is two sides of the same coin. One reflects the other, what do you think?" Let me walk you through this, so let's take a laggard. What is the technology look like? Is it based on 1990s BI and reporting largely parameterized reports on-premises data warehouses, or not even that operational reports, at best one enterprise data warehouse very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to. Or is there also a culture of fear, afraid of failure, resistance to change complacency and sometimes that complacency it's not because people are lazy, it's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and IT or individual stakeholders is the norm. So data is hoarded, let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics, search and AI-driven insights not on-premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data lake, and in a data warehouse, a logical data warehouse. The collaboration is being a newer methods whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust, there is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. There's none of this, oh, well, I didn't invent that, I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast, and they're energized, knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized, not just for power users or analysts, but really at the point of impact what we like to call the new decision makers. Or really the frontline workers. So Harvard business review partnered with us to develop this study to say, just how important is this? They've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager a warehouse manager, a financial services advisor. 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools, the sad reality only 20% of organizations are actually doing this, these are the data-driven leaders. So this is the culture and technology, how did we get here? It's because state of the art keeps changing. So the first generation BI and analytics platforms were deployed on-premises, on small datasets really just taking data out of ERP systems that were also on-premises, and state of the art was maybe getting a management report, an operational report. Over time visual based data discovery vendors, disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data sometimes coming from a data warehouse, the current state of the art though, Gartner calls it augmented analytics, at ThoughtSpot, we call it search and AI-driven analytics. And this was pioneered for large scale data sets, whether it's on-premises or leveraging the cloud data warehouses, and I think this is an important point. Oftentimes you, the data and analytics leaders, will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights, and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot I'll just show you what this looks like, instead of somebody's hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom getting to a visualization that then can be pinned to an existing Pinboard that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves. Modernizing the data and analytics portfolio is hard, because the pace of change has accelerated. You used to be able to create an investment, place a bet for maybe 10 years. A few years ago, that time horizon was five years, now it's maybe three years, and the time to maturity has also accelerated. So you have these different components the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI-driven insights. Competitors have followed suit, but be careful if you look at products like Power BI or SAP Analytics Cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift or Azure Synapse or Google BigQuery, they do not. They require you to move it into a smaller in memory engine. So it's important how well these new products inter operate. The pace of change, it's acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI, and that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you've read any of my books or used any of the maturity models out there whether the Gartner IT score that I worked on, or the data warehousing institute also has a maturity model. We talk about these five pillars to really become data-driven, as Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources. It's the talent, the people, the technology, and also the processes, and often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar, and in fact, in polls that we've done in these events, look at how much more important culture is, as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is, and let's take an example of where you can have great data but if you don't have the right culture there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years, but look at what happened in the face of negative news with data, that said, "Hey, we're not doing good cross selling, customers do not have both a checking account and a credit card and a savings account and a mortgage." They opened fake accounts, facing billions in fines, change in leadership, that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying that culture has not changed. Let's contrast that with some positive examples, Medtronic a worldwide company in 150 countries around the world, they may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes you know, this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients, they took the bold move of making their IP for ventilators publicly available, that is the power of a positive culture. Or Verizon, a major telecom organization, looking at late payments of their customers, and even though the US federal government said "Well, you can't turn them off." They said, "We'll extend that even beyond the mandated guidelines," and facing a slow down in the business because of the tough economy, he said, "You know what? We will spend the time upskilling our people giving them the time to learn more about the future of work, the skills and data and analytics," for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent identify the relevance, or I like to call it WIIFM, and organize for collaboration. So the CDO whatever your title is, chief analytics officer chief digital officer, you are the most important change agent. And this is where you will hear, that oftentimes a change agent has to come from outside the organization. So this is where, for example in Europe, you have the CDO of Just Eat takeout food delivery organization, coming from the airline industry or in Australia, National Australian Bank, taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in disrupt, it's a hard job. As one of you said to me, it often feels like Sisyphus, I make one step forward and I get knocked down again, I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIIFM, what is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline as well as those analysts, as well as the executives. So if we're talking about players in the NFL they want to perform better, and they want to stay safe. That is why data matters to them. If we're talking about financial services this may be a wealth management advisor, okay, we could say commissions, but it's really helping people have their dreams come true whether it's putting their children through college, or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers, you asked them about data, they'll say, "We don't need that, I care about the student." So if you can use data to help a student perform better that is WIIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. And we forget the impact on the people that it does require change. In fact, the Harvard Business Review Study, found that 44% said lack of change management is the biggest barrier to leveraging both new technology but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI Competency Center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model, centralized for economies of scale, that could be the common data, but then in bed, these evangelists, these analysts of the future, within every business unit, every functional domain, and as you see this top bar, all models are possible but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time, because data is helping organizations better navigate a tough economy lock in the customer loyalty, and I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at thought leaders, and next I'm pleased to introduce our first change agent Thomas Mazzaferro, chief data officer of Western Union, and before joining Western Union, Tom made his mark at HSBC and JP Morgan Chase spearheading digital innovation in technology operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (soft upbeat music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable, different business teams and technology teams into the future. As we look across our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive over the shift from a data standpoint, into the future. That includes being able to have the right information with the right quality of data at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that, as part of that partnership, and it's how we've looked to integrated into our overall business as a whole. We've looked at how do we make sure that our business and our professional lives, right? Are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go on to google.com or you go on to Bing, or go to Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability is allowed us to actually enable our overall business teams in our company, to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end users or the business executives, right? Search for what they need, what they want, at the exact time that action needed, to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology or our (indistinct) environments, and as we move that we've actually picked to our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive into organize our information and our data, then drive these new solutions and capabilities forward. So big portion of us though is culture, so how do we engage with the business teams and bring the IT teams together to really drive these holistic end to end solutions and capabilities, to really support the actual business into the future. That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven, this is the key. If you can really start to provide answers to business questions before they're even being asked, and to predict based upon different economic trends or different trends in your business, what does is be made and actually provide those answers to the business teams before they're even asking for it. That is really becoming a data-driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, based upon products, solutions, or partnerships into the future. These are really some of the keys that become crucial as you move forward right into this new age, especially with COVID, with COVID now taking place across the world, right? Many of these markets, many of these digital transformations are celebrating, and are changing rapidly to accommodate and to support customers in these very difficult times. As part of that, you need to make sure you have the right underlying foundation, ecosystems and solutions to really drive those capabilities, and those solutions forward. As we go through this journey, both of my career but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only a celebrating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes both on the platform standpoint, tools, but also what our customers want, what do our customers need, and how do we then surface them with our information, with our data, with our platform, with our products and our services, to meet those needs and to really support and service those customers into the future. This is all around becoming a more data-driven organization such as how do you use your data to support the current business lines. But how do you actually use your information your data, to actually better support your customers better support your business, better support your employees, your operations teams and so forth, and really creating that full integration in that ecosystem is really when you start to get large dividends from these investments into the future. With that being said I hope you enjoyed the segment on how to become and how to drive a data-driven organization, and looking forward to talking to you again soon, thank you. >> Tom, that was great, thanks so much. Now I'm going to have to brag on you for a second, as a change agent you've come in disrupted, and how long have you been at Western Union? >> Only nine months, I just started this year, but there'd be some great opportunities and big changes, and we have a lot more to go, but we're really driving things forward in partnership with our business teams, and our colleagues to support those customers forward. >> Tom, thank you so much that was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent. Most recently with Schneider Electric, but even going back to Sam's Club, Gustavo welcome. (soft upbeat music) >> So hi everyone my name is Gustavo Canton and thank you so much Cindi for the intro. As you mentioned, doing transformations is a you know, high effort, high reward situation. I have empowerment in transformation and I have led many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North Star and you know where you're going, the one thing that I want you to take away from this discussion today, is that you need to be bold to evolve. And so in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are nontraditional sometimes. And so how do we get started? So I think the answer to that is, you have to start for you, yourself as a leader and stay tuned. And by that, I mean you need to understand not only what is happening in your function or your field, but you have to be very into what is happening in society, socioeconomically speaking, wellbeing, you know, the common example is a great example. And for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential, for customers and communities to grow, wellbeing should be at the center of every decision. And as somebody mentioned, it's great to be you know, stay in tune and have the skillset and the courage. But for me personally, to be honest to have this courage is not about not being afraid. You're always afraid when you're making big changes and your swimming upstream. But what gives me the courage is the empathy part, like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business, and what the leaders are trying to do, what I do it thinking about the mission of how do I make change for the bigger, you know workforce so the bigger good, despite the fact that this might have a perhaps implication, so my own self interest in my career, right? Because you have to have that courage sometimes to make choices, that are not well seeing politically speaking what are the right thing to do, and you have to push through it. So the bottom line for me is that, I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past, and what they show is that if you look at the four main barriers, that are basically keeping us behind budget, inability to add, cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, this topic about culture is actually gaining more and more traction, and in 2018, there was a story from HBR and it was for about 45%. I believe today, it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand, and are aware that we need to transform, commit to the transformation and set us deadline to say, "Hey, in two years, we're going to make this happen, what do we need to do to empower and enable these search engines to make it happen?" You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you samples of some of the roadblocks that I went through, as I think the intro information most recently as Cindi mentioned in Schneider. There are three main areas, legacy mindset, and what that means is that we've been doing this in a specific way for a long time, and here is how we have been successful. We're working the past is not going to work now, the opportunity there is that there is a lot of leaders who have a digital mindset, and their up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people you know, three to five years for them to develop, because the world is going to in a way that is super fast. The second area and this is specifically to implementation of AI is very interesting to me, because just example that I have with ThoughtSpot, right? We went to an implementation and a lot of the way the IT team functions, so the leaders look at technology, they look at it from the prism of the prior or success criteria for the traditional BIs, and that's not going to work. Again, your opportunity here is that you need to really find what success look like, in my case, I want the user experience of our workforce to be the same as your experience you have at home. It's a very simple concept, and so we need to think about how do we gain that user experience with this augmented analytics tools, and then work backwards to have the right talent, processes and technology to enable that. And finally, and obviously with COVID a lot of pressure in organizations and companies to do more with less, and the solution that most leaders I see are taking is to just minimize cost sometimes and cut budget. We have to do the opposite, we have to actually invest some growth areas, but do it by business question. Don't do it by function, if you actually invest in these kind of solutions, if you actually invest on developing your talent, your leadership, to see more digitally, if you actually invest on fixing your data platform is not just an incremental cost, it's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work in working very hard but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there, and you just to put it into some perspective, there have been some studies in the past about you know, how do we kind of measure the impact of data? And obviously this is going to vary by organization, maturity there's going to be a lot of factors. I've been in companies who have very clean, good data to work with, and I think with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study what I think is interesting is, they try to put a tagline or attack price to what is a cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work, when you have data that is flawed as opposed to have imperfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be a $100. But now let's say you have any percent perfect data and 20% flow data, by using this assumption that flow data is 10 times as costly as perfect data, your total costs now becomes $280 as opposed to $100, this just for you to really think about as a CIO, CTO, you know CSRO, CEO, are we really paying attention and really closing the gaps that we have on our infrastructure? If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact, but as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these barriers, right? I think the key is I am in analytics, I know statistics obviously, and love modeling and you know, data and optimization theory and all that stuff, that's what I can do analytics, but now as a leader and as a change agent, I need to speak about value, and in this case, for example for Schneider, there was this tagline coffee of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the right leaders, because you need to, you know, focus on the leaders that you're going to make the most progress. You know, again, low effort, high value, you need to make sure you centralize all the data as you can, you need to bring in some kind of augmented analytics, you know, solution, and finally you need to make it super simple for the you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation but it was two years for this component of augmented analytics. It took about two years to talk to, you know, IT, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics, I pulled up, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers, but one thing that is really important is as you bring along your audience on this, you know, you're going from Excel, you know in some cases or Tableau to other tools like you know, ThoughtSpot, you need to really explain them, what is the difference, and how these two can truly replace some of the spreadsheets or some of the views that you might have on these other kind of tools. Again, Tableau, I think it's a really good tool, there are other many tools that you might have in your toolkit. But in my case, personally I feel that you need to have one portal going back to seeing these points that really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to these stations. Like I said it's been years for us to kind of lay the foundation, get the leadership and chasing culture, so people can understand why you truly need to invest what I meant analytics. And so what I'm showing here is an example of how do we use basically, you know a tool to capturing video, the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, hours saved, user experience and adoption. So for hours saved, our ambition was to have 10 hours per week per employee save on average, user experience or ambition was 4.5 and adoption 80%. In just two months, two months and a half of the pilot we were able to achieve five hours, per week per employee savings. I used to experience for 4.3 out of five, and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications obviously the operations things and the users, in HR safety and other areas that might be basically stakeholders in this whole process. So just to summarize this kind of effort takes a lot of energy, you are a change agent, you need to have a courage to make these decision and understand that, I feel that in this day and age with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very souls for this organization, and that gave me the confidence to know that the work has been done, and we are now in a different stage for the organization. And so for me it safe to say, thank you for everybody who has believed obviously in our vision, everybody who has believed in, you know, the word that we were trying to do and to make the life for, you know workforce or customers that are in community better. As you can tell, there is a lot of effort, there is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied with the accomplishments of this transformation, and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream you know, what would mentors what people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort but is well worth it. And with that said, I hope you are well and it's been a pleasure talking to you, talk to you soon, take care. >> Thank you Gustavo, that was amazing. All right, let's go to the panel. (soft upbeat music) >> I think we can all agree how valuable it is to hear from practitioners, and I want to thank the panel for sharing their knowledge with the community, and one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top, why? Because it directs the middle, and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard, is that you all prioritize database decision making in your organizations, and you combine two of your most valuable assets to do that, and create leverage, employees on the front lines, and of course the data. That was rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it, well COVID's broken everything. And it's great to hear from our experts, you know, how to move forward, so let's get right into it. So Gustavo let's start with you if I'm an aspiring change agent, and let's say I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >> I think curiosity is very important. You need to be, like I say, in tune to what is happening not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business as you know, I come from, you know, Sam's Club Walmart retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement that's just going to take you so far. What you have to do is and that's what I tried to do is I try to go into areas, businesses and transformations that make me, you know stretch and develop as a leader. That's what I'm looking to do, so I can help transform the functions organizations, and do these change management and decisions mindset as required for these kinds of efforts. >> Thank you for that is inspiring and Cindi, you love data, and the data is pretty clear that diversity is a good business, but I wonder if you can add your perspectives to this conversation. >> Yeah, so Michelle has a new fan here because she has found her voice, I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad, so he did teach me how to work in a predominantly male environment. But why I think diversity matters more now than ever before, and this is by gender, by race, by age, by just different ways of working and thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models, and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority, you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible >> Great perspectives thank you, Tom, I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth actually you know, in a digital business over the last 12 months really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers and today, that there's been a huge need, right? To send money, to support family, to support friends and loved ones across the world. And as part of that, you know, we are very honored to support those customers that we across all the centers today. But as part of that celebration, we need to make sure that we had the right architecture and the right platforms to basically scale, right? To basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did celebrate some of our plans on digital to help support that overall growth coming in, and to support our customers going forward. Because there were these times during this pandemic, right? This is the most important time, and we need to support those that we love and those that we care about. And in doing that, it's one of those ways is actually by sending money to them, support them financially. And that's where really are part of that our services come into play that, you know, I really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this level, and supporting our business going forward. >> Awesome, thank you. Now I want to come back to Gustavo, Tom, I'd love for you to chime in too. Did you guys ever think like you were pushing the envelope too much and doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing, or you pushing your people too hard, can you share that experience and how you got through it? >> Yeah, the way I look at it is, you know, again, whenever I go to an organization I ask the question, Hey, how fast you would like to conform?" And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions and I collaborate in a specific way. Now, in the case of COVID, for example, right? It forces us to remove silos and collaborate in a faster way, so to me it was an opportunity to actually integrate with other areas and drive decisions faster. But make no mistake about it, when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay, you know debating points or making repetitive business cases onto people connect with the decision because you understand, and you are seeing that, hey, the CEO is making a one, two year, you know, efficiency goal, the only way for us to really do more with less is for us to continue this path. We cannot just stay with the status quo, we need to find a way to accelerate transformation... >> How about you Tom, we were talking earlier was Sudheesh had said about that bungee jumping moment, what can you share? >> Yeah you know, I think you hit upon it. Right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right? That's what I tell my team is that you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right? Expand and support that the ever changing needs the marketplace and industry and our customers today and that pace of change that's happening, right? And what customers are asking for, and the competition the marketplace, it's only going to accelerate. So as part of that, you know, as we look at what how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan into align, to drive the actual transformation, so that you can scale even faster into the future. So as part of that, so we're putting in place here, right? Is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> We're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindi, last question, you've worked with hundreds of organizations, and I got to believe that you know, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. You know, they're not on my watch for whatever variety of reasons, but it's being forced on them now, but knowing what you know now that you know, we're all in this isolation economy how would you say that advice has changed, has it changed? What's your number one action and recommendation today? >> Yeah well, first off, Tom just freaked me out. What do you mean this is the slowest ever? Even six months ago, I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, very aware of the power in politics and how to bring people along in a way that they are comfortable, and now I think it's, you know what? You can't get comfortable. In fact, we know that the organizations that were already in the cloud, have been able to respond and pivot faster. So if you really want to survive as Tom and Gustavo said, get used to being uncomfortable, the power and politics are going to happen. Break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's Sudheesh going to go on bungee jumping? (all chuckling) >> That's fantastic discussion really. Thanks again to all the panelists and the guests, it was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in theCUBE program recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just as I said before lip service. And sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done right, the right culture is going to deliver tremendous results. Yeah, what does that mean getting it right? Everybody's trying to get it right. My biggest takeaway today, is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions that can drive you revenue, cut costs, speed, access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay, let's bring back Sudheesh and wrap things up. Sudheesh please bring us home. >> Thank you, thank you Dave, thank you theCUBE team, and thanks goes to all of our customers and partners who joined us, and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I was simply put it, she said it really well, that is be brave and drive. Don't go for a drive along, that is such an important point. Often times, you know that I think that you have to do to make the positive change that you want to see happen. But you wait for someone else to do it, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk. Cindi talked about finding the importance of finding your voice, taking that chair, whether it's available or not and making sure that your ideas, your voices are heard and if it requires some force then apply that force, make sure your ideas are good. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the courtroom. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom instead of a single take away, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in, and they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to thoughtspot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is, please go to thoughtspot.com/beyond, our global user conferences happening in this December, we would love to have you join us. It's again, virtual, you can join from anywhere, we are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we would have been up to since the last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing, you'll be sharing things that you have been working to release something that will come out next year. And also some of the crazy ideas for engineers I've been cooking up. All of those things will be available for you at ThoughtSpot Beyond, thank you, thank you so much.

(speaks in foreign language) >> Narrator: Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent, and cultural change. Empowering everyone on the front lines to make decisions, all at the speed of digital. The transformation starts with you. It's time to lead the way, it's time for thought leaders. >> Welcome to Thought Leaders, a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis, and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core, requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today, we're going to hear from experienced leaders, who are transforming their organizations with data, insights and creating digital-first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot. First, Chief Data Strategy Officer for ThoughtSpot is Cindi Hausen. Cindi is an analytics and BI expert with 20 plus years experience and the author of Successful Business Intelligence Unlock The Value of BI and Big Data. Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you, welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of theCUBE is ThoughtSpot CEO Sudheesh Nair. Hello Sudheesh, how are you doing today? >> I am well Dave, it's good to talk to you again. >> It's great to see you. Thanks so much for being here. Now Sudheesh, please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today? (gentle music) >> Thanks, Dave, I wish you were there to introduce me into every room that I walk into because you have such an amazing way of doing it. It makes me feel also good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our, you know, sort of effort to reach out to you with invites for events like this. So we are getting way more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time, and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, and generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, you know, we are living through these difficult times, we want an event to be, this event to be more of an uplifting and inspiring event too. Now, the challenge is, how do you do that with the team being change agents? Because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do or likes to do. The way I think of it, change is sort of like, if you've ever done bungee jumping. You know, it's like standing on the edges, waiting to make that one more step. You know, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage and when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation, in most businesses it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to to, first of all, challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that, "You know, maybe I don't have the power to make the change that the company needs. Sometimes I feel like I don't have the skills." Sometimes they may feel that, I'm probably not the right person to do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. You know, there are people in the company, who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data, they have the skills to do that, but they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is this silo of people with the answers and there is a silo of people with the questions, and there is gap. These sort of silos are standing in the way of making that necessary change that we all I know the business needs, and the last change to sort of bring an external force sometimes. It could be a tool, it could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is. You may need to bring some external stimuli to start that domino of the positive changes that are necessary. The group of people that we have brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to trust the rope that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading her bio, that there are no country vital worldwide competition for cool patents, because she will beat all of us because when her children were small, you know, they were probably into Harry Potter and Disney and she was managing a business and leading change there. And then as her kids grew up and got to that age, where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom. I am extremely excited to see what she's going to talk about. I've seen the slides with a bunch of amazing pictures, I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle. I'm looking forward to her talk next. Welcome Michelle. It's over to you. (gentle music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. This is about as close as I'm ever going to get. So, I want to talk to you about quarterbacking our digital revolution using insights, data and of course, as you said, leadership. First, a little bit about myself, a little background. As I said, I always wanted to play football and this is something that I wanted to do since I was a child but when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent and in the South football is like a religion and you pick sides. I chose Auburn University working in the athletic department, so I'm testament. Till you can start, a journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well not actually not so little, he played offensive line for the Alabama Crimson Tide. And for those of you who know SEC football, you know this is a really big rivalry, and when you choose sides your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL, he just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight. From Universal Studios, Disney, to my current position as CIO of the NFL. In this job, I'm very privileged to have the opportunity to work with a team that gets to bring America's game to millions of people around the world. Often, I'm asked to talk about how to create amazing experiences for fans, guests or customers. But today, I really wanted to focus on something different and talk to you about being behind the scenes and backstage. Because behind every event, every game, every awesome moment, is execution. Precise, repeatable execution and most of my career has been behind the scenes doing just that. Assembling teams to execute these plans and the key way that companies operate at these exceptional levels is making good decisions, the right decisions, at the right time and based upon data. So that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves, and it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kind of world class experiences are often seeking out and leveraging next generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute. A little bit first about Disney. In '90s I was at Disney leading a project called Destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool and then certainly before anything like a data-driven culture was ever brought up. But way back then we were creating a digital backbone that enabled many technologies for the things that you see today. Like the MagicBand, Disney's Magical Express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data, more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately, leading to moving into IT and I haven't looked back since. In the early 2000s, I was at Universal Studio's theme park as their CIO preparing for and launching the Wizarding World of Harry Potter. Bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wand selects you at a wand shop. As today at the NFL, I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning and all new communication strategies, and using data to drive everything, from player performance, contracts, to where we build new stadiums and hold events. With this year being the most challenging, yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contact tracing devices joined with testing data. Talk about data actually enabling your business. Without it we wouldn't be having a season right now. I'm also on the board of directors of two public companies, where data and collaboration are paramount. First, RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone, all-in-one solution in the cloud and Quotient Technologies, whose product is actually data. The tagline at Quotient is The Result in Knowing. I think that's really important because not all of us are data companies, where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First, just hit on it, is change. how to be a champion and a driver of change. Second, how to use data to drive performance for your company and measure performance of your company. Third, how companies now require intense collaboration to operate and finally, how much of this is accomplished through solid data-driven decisions. First, let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it. And thankfully, for the most part, knock on wood, we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, The 2020 Draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage, to smaller events in club facilities. And then ultimately, to one where everyone coaches, GMs, prospects and even our commissioner were at home in their basements and we only had a few weeks to figure it out. I found myself for the first time, being in the live broadcast event space. Talking about bungee jumping, this is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary, it was certainly very risky, but it ended up being also rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at its level, highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field, you can see points being scored and stats, and you immediately know that impact. Those with the best stats usually win the games. The NFL has always recorded stats. Since the beginning of time here at the NFL a little... This year is our 101st year and athlete's ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured and I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled recently. And how fast do you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys to the data and the use of the data. Our next generation stats platform is taking data to the next level. It's powered by Amazon Web Services and we gather this data, real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course, it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize, route patterns, speed, match-ups, et cetera, so much faster than ever before. We're continuing to roll out sensors too, that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about, for those of you that are IT professionals and developers, you know, more than 10 years ago agile practices began sweeping companies. Where small teams would work together rapidly in a very flexible, adaptive and innovative way and it proved to be transformational. However today, of course that is no longer just small teams, the next big wave of change and we've seen it through this pandemic, is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you got the people from the bottom up to do it and you executed. At Universal, we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties, so influence and collaboration, and how to share across companies became very important. And now here I am at the NFL an even the bigger ecosystem. We have 32 clubs that are all separate businesses, 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company but across companies. The ability to work in a collaborative way across businesses and even other companies, that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation, yet competition to co-exist. I mean, the NFL is a great example of what we call co-oppetition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data-driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units, who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be, data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask? It's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with, first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program, it's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, thank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an a line person. >> Well, then I can't do my job without you. >> Great and I'm getting the feeling now, you know, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take him to the Delaware Water Gap and we do the cliff jumping. >> Oh that sounds good, I'll watch your watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders, when you're trying to prioritize the different voices you have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there are so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with aligning on a mission and if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together. You sort of do get them to naturally prioritize their work and I think that's very important. So for us at the NFL and even at Disney, it was our core values and our core purpose is so well known and when anything challenges that, we're able to sort of lay that out. But as a change agent, you have to be very empathetic, and I would say empathy is probably your strongest skill if you're a change agent and that means listening to every single stakeholder. Even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic, and having a mission, and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling, so thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. >> (gentle music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl, what went wrong? 1986, as the reactors were melting down, they had the data to say, "This is going to be catastrophic," and yet the culture said, "No, we're perfect, hide it. Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again. This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with and this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology, is it really two sides of the same coin? Real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "You know, Cindi, I actually think this is two sides of the same coin, one reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting, largely parametrized reports, on-premises data warehouses, or not even that operational reports. At best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change, complacency. And sometimes that complacency, it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, "No, we're measured on least to serve." So politics and distrust, whether it's between business and IT or individual stakeholders is the norm, so data is hoarded. Let's contrast that with the leader, a data and analytics leader, what does their technology look like? Augmented analytics, search and AI driven insights, not on-premises but in the cloud and maybe multiple clouds. And the data is not in one place but it's in a data lake and in a data warehouse, a logical data warehouse. The collaboration is via newer methods, whether it's Slack or Teams, allowing for that real-time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals. Whether it's the best fan experience and player safety in the NFL or best serving your customers, it's innovative and collaborative. There's none of this, "Oh, well, I didn't invent that. I'm not going to look at that." There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas, to fail fast and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized, not just for power users or analysts, but really at the point of impact, what we like to call the new decision-makers or really the frontline workers. So Harvard Business Review partnered with us to develop this study to say, "Just how important is this? We've been working at BI and analytics as an industry for more than 20 years, why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor." 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture and technology, how did we get here? It's because state-of-the-art keeps changing. So the first generation BI and analytics platforms were deployed on-premises, on small datasets, really just taking data out of ERP systems that were also on-premises and state-of-the-art was maybe getting a management report, an operational report. Over time, visual based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state-of-the-art though, Gartner calls it augmented analytics. At ThoughtSpot, we call it search and AI driven analytics, and this was pioneered for large scale data sets, whether it's on-premises or leveraging the cloud data warehouses. And I think this is an important point, oftentimes you, the data and analytics leaders, will look at these two components separately. But you have to look at the BI and analytics tier in lock-step with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding a report, it's typing in search keywords and very robust keywords contains rank, top, bottom, getting to a visual visualization that then can be pinned to an existing pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non-analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You used to be able to create an investment, place a bet for maybe 10 years. A few years ago, that time horizon was five years. Now, it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization but I would also say, equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful, if you look at products like Power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure Synapse, or Google BigQuery, they do not. They require you to move it into a smaller in-memory engine. So it's important how well these new products inter-operate. The pace of change, its acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI and that is roughly three times the prediction they had just a couple of years ago. So let's talk about the real world impact of culture and if you've read any of my books or used any of the maturity models out there, whether the Gartner IT Score that I worked on or the Data Warehousing Institute also has a maturity model. We talk about these five pillars to really become data-driven. As Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology and also the processes. And often when I would talk about the people in the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders. You have told me now culture is absolutely so important, and so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say I have been a loyal customer of Wells Fargo for more than 20 years, but look at what happened in the face of negative news with data. It said, "Hey, we're not doing good cross-selling, customers do not have both a checking account and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture and they're trying to fix this, but even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples. Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers and even though the U.S. Federal Government said, "Well, you can't turn them off." They said, "We'll extend that even beyond the mandated guidelines," and facing a slow down in the business because of the tough economy, They said, "You know what? We will spend the time upskilling our people, giving them the time to learn more about the future of work, the skills and data and analytics for 20,000 of their employees rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions. Bring in a change agent, identify the relevance or I like to call it WIIFM and organize for collaboration. So the CDO, whatever your title is, Chief Analytics Officer, Chief Digital Officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe you have the CDO of Just Eat, a takeout food delivery organization coming from the airline industry or in Australia, National Australian Bank taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in, disrupt. It's a hard job. As one of you said to me, it often feels like. I make one step forward and I get knocked down again, I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIIFM What's In It For Me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So, if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay, we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers you ask them about data. They'll say, "We don't need that, I care about the student." So if you can use data to help a student perform better, that is WIIFM and sometimes we spend so much time talking the technology, we forget, what is the value we're trying to deliver with this? And we forget the impact on the people that it does require change. In fact, the Harvard Business Review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then embed these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time because data is helping organizations better navigate a tough economy, lock in the customer loyalty and I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next, I'm pleased to introduce our first change agent, Tom Mazzaferro Chief Data Officer of Western Union and before joining Western Union, Tom made his Mark at HSBC and JP Morgan Chase spearheading digital innovation in technology, operations, risk compliance and retail banking. Tom, thank you so much for joining us today. (gentle music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and the technology teams into the future? As we look across our data ecosystems and our platforms, and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive an organization from a data standpoint, into the future. That includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot to actually bring in the technology to help us drive that. As part of that partnership and it's how we've looked to integrate it into our overall business as a whole. We've looked at, how do we make sure that our business and our professional lives, right? Are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go onto Bing or you go onto Yahoo and you search for what you want, search to find an answer. ThoughtSpot for us is the same thing, but in the business world. So using ThoughtSpot and other AI capability is it's allowed us to actually enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone, or an engineer to go pull information or pull data. We actually can have the end users or the business executives, right. Search for what they need, what they want, at the exact time that they actually need it, to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on a journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, our... The local environments and as we move that, we've actually picked two of our cloud providers going to AWS and to GCP. We've also adopted Snowflake to really drive and to organize our information and our data, then drive these new solutions and capabilities forward. So a big portion of it though is culture. So how do we engage with the business teams and bring the IT teams together, to really help to drive these holistic end-to-end solutions and capabilities, to really support the actual business into the future. That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven. This is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what decisions need to be made and actually provide those answers to the business teams before they're even asking for it. That is really becoming a data-driven organization and as part of that, it really then enables the business to act quickly and take advantage of opportunities as they come in based upon industries, based upon markets, based upon products, solutions or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, Especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are celebrating and are changing rapidly to accommodate and to support customers in these very difficult times. As part of that, you need to make sure you have the right underlying foundation, ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both in my career but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes, both on the platform standpoint, tools, but also what do our customers want, what do our customers need and how do we then service them with our information, with our data, with our platform, and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data-driven organization, such as how do you use your data to support your current business lines, but how do you actually use your information and your data to actually better support your customers, better support your business, better support your employees, your operations teams and so forth. And really creating that full integration in that ecosystem is really when you start to get large dividends from these investments into the future. With that being said, I hope you enjoyed the segment on how to become and how to drive a data-driven organization, and looking forward to talking to you again soon. Thank you. >> Tom, that was great. Thanks so much and now going to have to drag on you for a second. As a change agent you've come in, disrupted and how long have you been at Western Union? >> Only nine months, so just started this year, but there have been some great opportunities to integrate changes and we have a lot more to go, but we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now, I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe and he is a serial change agent. Most recently with Schneider Electric but even going back to Sam's Clubs. Gustavo, welcome. (gentle music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro. As you mentioned, doing transformations is, you know, a high reward situation. I have been part of many transformations and I have led many transformations. And, what I can tell you is that it's really hard to predict the future, but if you have a North Star and you know where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so, in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started, barriers or opportunities as I see it, the value of AI and also, how you communicate. Especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so, how do we get started? So, I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand, not only what is happening in your function or your field, but you have to be very in tune what is happening in society socioeconomically speaking, wellbeing. You know, the common example is a great example and for me personally, it's an opportunity because the number one core value that I have is wellbeing. I believe that for human potential for customers and communities to grow, wellbeing should be at the center of every decision. And as somebody mentioned, it's great to be, you know, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes and you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. But I do it thinking about the mission of, how do I make change for the bigger workforce or the bigger good despite the fact that this might have perhaps implication for my own self interest in my career. Right? Because you have to have that courage sometimes to make choices that are not well seen, politically speaking, but are the right thing to do and you have to push through it. So the bottom line for me is that, I don't think we're they're transforming fast enough. And the reality is, I speak with a lot of leaders and we have seen stories in the past and what they show is that, if you look at the four main barriers that are basically keeping us behind budget, inability to act, cultural issues, politics and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topic about culture is actually gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today, it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a deadline to say, "Hey, in two years we're going to make this happen. What do we need to do, to empower and enable these change agents to make it happen? You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So, I'll give you examples of some of the roadblocks that I went through as I've been doing transformations, most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset and what that means is that, we've been doing this in a specific way for a long time and here is how we have been successful. What worked in the past is not going to work now. The opportunity there is that there is a lot of leaders, who have a digital mindset and they're up and coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these talents, including young talent. We cannot be thinking in the past and just wait for people, you know, three to five years for them to develop because the world is going in a way that is super-fast. The second area and this is specifically to implementation of AI. It's very interesting to me because just the example that I have with ThoughtSpot, right? We went on implementation and a lot of the way the IT team functions or the leaders look at technology, they look at it from the prism of the prior or success criteria for the traditional BIs, and that's not going to work. Again, the opportunity here is that you need to redefine what success look like. In my case, I want the user experience of our workforce to be the same user experience you have at home. It's a very simple concept and so we need to think about, how do we gain that user experience with these augmented analytics tools and then work backwards to have the right talent, processes, and technology to enable that. And finally and obviously with COVID, a lot of pressure in organizations and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs sometimes and cut budget. We have to do the opposite. We have to actually invest on growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent and your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard but it's not efficient and it's not working in the way that you might want to work. So there is a lot of opportunity there and just to put in terms of perspective, there have been some studies in the past about, you know, how do we kind of measure the impact of data? And obviously, this is going to vary by organization maturity, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with and I've been with companies that we have to start basically from scratch. So it all depends on your maturity level. But in this study, what I think is interesting is they try to put a tagline or a tag price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to having perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have 80% perfect data and 20% flawed data. By using this assumption that flawed data is 10 times as costly as perfect data, your total costs now becomes $280 as opposed to $100. This just for you to really think about as a CIO, CTO, you know CHRO, CEO, "Are we really paying attention and really closing the gaps that we have on our data infrastructure?" If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact, but as you can tell, the price tag goes up very, very quickly. So now, if I were to say, how do I communicate this or how do I break through some of these challenges or some of these barriers, right? I think the key is, I am in analytics, I know statistics obviously and love modeling, and, you know, data and optimization theory, and all that stuff. That's what I came to analytics, but now as a leader and as a change agent, I need to speak about value and in this case, for example, for Schneider. There was this tagline, make the most of your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that, I understood what kind of language to use, how to connect it to the overall strategy and basically, how to bring in the right leaders because you need to, you know, focus on the leaders that you're going to make the most progress, you know. Again, low effort, high value. You need to make sure you centralize all the data as you can, you need to bring in some kind of augmented analytics, you know, solution. And finally, you need to make it super-simple for the, you know, in this case, I was working with the HR teams and other areas, so they can have access to one portal. They don't have to be confused and looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to, you know, IT, get leadership support, find the budgeting, you know, get everybody on board, make sure the success criteria was correct. And we call this initiative, the people analytics portal. It was actually launched in July of this year and we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many, many factors but one thing that is really important is as you bring along your audience on this, you know. You're going from Excel, you know, in some cases or Tableu to other tools like, you know, ThoughtSpot. You need to really explain them what is the difference and how this tool can truly replace some of the spreadsheets or some of the views that you might have on these other kinds of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit but in my case, personally, I feel that you need to have one portal. Going back to Cindi's points, that really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory and I will tell you why, because it took a lot of effort for us to get to this stage and like I said, it's been years for us to kind of lay the foundation, get the leadership, initiating culture so people can understand, why you truly need to invest on augmented analytics. And so, what I'm showing here is an example of how do we use basically, you know, a tool to capturing video, the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics. Hours saved, user experience and adoption. So for hours saved, our ambition was to have 10 hours per week for employee to save on average. User experience, our ambition was 4.5 and adoption 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings, a user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations things and the users. In HR safety and other areas that might be basically stakeholders in this whole process. So just to summarize, this kind of effort takes a lot of energy. You are a change agent, you need to have courage to make this decision and understand that, I feel that in this day and age with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these great resource for this organization and that give me the confident to know that the work has been done and we are now in a different stage for the organization. And so for me, it's just to say, thank you for everybody who has belief, obviously in our vision, everybody who has belief in, you know, the work that we were trying to do and to make the life of our, you know, workforce or customers and community better. As you can tell, there is a lot of effort, there is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied with the accomplishments of this transformation and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream, you know, work with mentors, work with people in the industry that can help you out and guide you on this kind of transformation. It's not easy to do, it's high effort, but it's well worth it. And with that said, I hope you are well and it's been a pleasure talking to you. Talk to you soon. Take care. >> Thank you, Gustavo. That was amazing. All right, let's go to the panel. (light music) Now I think we can all agree how valuable it is to hear from practitioners and I want to thank the panel for sharing their knowledge with the community. Now one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision making in your organizations. And you combine two of your most valuable assets to do that and create leverage, employees on the front lines, and of course the data. Now as as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. You know, the old saying, if it ain't broke, don't fix it, well COVID has broken everything and it's great to hear from our experts, you know, how to move forward, so let's get right into it. So Gustavo, let's start with you. If I'm an aspiring change agent and let's say I'm a budding data leader, what do I need to start doing? What habits do I need to create for long-lasting success? >> I think curiosity is very important. You need to be, like I said, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I've been doing it for 50 years plus, but I think you need to understand wellbeing of the areas across not only a specific business. As you know, I come from, you know, Sam's Club, Walmart retail. I've been in energy management, technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to just continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do, is I try to go into areas, businesses and transformations, that make me, you know, stretch and develop as a leader. That's what I'm looking to do, so I can help transform the functions, organizations, and do the change management, the essential mindset that's required for this kind of effort. >> Well, thank you for that. That is inspiring and Cindi you love data and the data is pretty clear that diversity is a good business, but I wonder if you can, you know, add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine and it's interesting because I was raised by my dad, a single dad, so he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before and this is by gender, by race, by age, by just different ways of working and thinking, is because as we automate things with AI, if we do not have diverse teams looking at the data, and the models, and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are, finding your voice, having a seat at the table and just believing in the impact of your work has never been more important and as Michelle said, more possible. >> Great perspectives, thank you. Tom, I want to go to you. So, I mean, I feel like everybody in our businesses is in some way, shape, or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth, actually, in our digital business over the last 12 months really, even acceleration, right, once COVID hit. We really saw that in the 200 countries and territories that we operate in today and service our customers in today, that there's been a huge need, right, to send money to support family, to support friends, and to support loved ones across the world. And as part of that we are very honored to be able to support those customers that, across all the centers today, but as part of the acceleration, we need to make sure that we have the right architecture and the right platforms to basically scale, right? To basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because during these times, during this pandemic, right, this is the most important time and we need to support those that we love and those that we care about. And doing that some of those ways is actually by sending money to them, support them financially. And that's where really our products and our services come into play that, you know, and really support those families. So, it was really a great opportunity for us to really support and really bring some of our products to the next level and supporting our business going forward. >> Awesome, thank you. Now, I want to come back to Gustavo. Tom, I'd love for you to chime in too. Did you guys ever think like you were pushing the envelope too much in doing things with data or the technology that it was just maybe too bold, maybe you felt like at some point it was failing, or you're pushing your people too hard? Can you share that experience and how you got through it? >> Yeah, the way I look at it is, you know, again, whenever I go to an organization, I ask the question, "Hey, how fast you would like to conform?" And, you know, based on the agreements on the leadership and the vision that we want to take place, I take decisions and I collaborate in a specific way. Now, in the case of COVID, for example, right, it forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it, when you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension or you need to be okay, you know, debating points or making repetitive business cases until people connect with the decision because you understand and you are seeing that, "Hey, the CEO is making a one, two year, you know, efficiency goal. The only way for us to really do more with less is for us to continue this path. We can not just stay with the status quo, we need to find a way to accelerate the transformation." That's the way I see it. >> How about Utah, we were talking earlier with Sudheesh and Cindi about that bungee jumping moment. What can you share? >> Yeah, you know, I think you hit upon it. Right now, the pace of change will be the slowest pace that you see for the rest of your career. So as part of that, right, this is what I tell my team, is that you need to be, you need to feel comfortable being uncomfortable. Meaning that we have to be able to basically scale, right? Expand and support the ever changing needs in the marketplace and industry and our customers today, and that pace of change that's happening, right? And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, you know, as you look at how you're operating today in your current business model, right? Things are only going to get faster. So you have to plan and to align and to drive the actual transformation, so that you can scale even faster into the future. So it's part of that, that's what we're putting in place here, right? It's how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So Cindi, last question, you've worked with hundreds of organizations and I got to believe that, you know, some of the advice you gave when you were at Gartner, which was pre-COVID, maybe sometimes clients didn't always act on it. You know, not my watch or for whatever, variety of reasons, but it's being forced on them now. But knowing what you know now that, you know, we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well first off, Tom, just freaked me out. What do you mean, this is the slowest ever? Even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more very aware of the power in politics and how to bring people along in a way that they are comfortable and now I think it's, you know what, you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So, if you really want to survive, as Tom and Gustavo said, get used to being uncomfortable. The power and politics are going to happen, break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where Sudheesh is going to go bungee jumping. (all chuckling) >> Guys, fantastic discussion, really. Thanks again to all the panelists and the guests, it was really a pleasure speaking with you today. Really, virtually all of the leaders that I've spoken to in theCUBE program recently, they tell me that the pandemic is accelerating so many things. Whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise-wide digital transformation, not just as I said before, lip service. You know, sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done right, the right culture is going to deliver tournament results. You know, what does that mean? Getting it right. Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization, data can create insights and informed decisions that drive value. Okay, let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you, thank you, Dave. Thank you, theCUBE team, and thanks goes to all of our customers and partners who joined us, and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I heard from all four of our distinguished speakers. First, Michelle, I will simply put it, she said it really well. That is be brave and drive, don't go for a drive alone. That is such an important point. Often times, you know the right thing that you have to do to make the positive change that you want to see happen, but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I picked up from Michelle's talk. Cindi talked about finding, the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voice is heard and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes. The importance of building the quorum, and that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in and they were able to make the change that is necessary through this difficult time in a matter of months. If they could do it, anyone could. The second thing I want to do is to leave you with a takeaway, that is I would like you to go to ThoughtSpot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is, please go to ThoughtSpot.com/beyond. Our global user conference is happening in this December. We would love to have you join us, it's, again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we have been working to release, something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at ThoughtSpot Beyond. Thank you, thank you so much.

>> Data is at the heart of transformation and the change every company needs to succeed, but it takes more than new technology. It's about teams, talent and cultural change. Empowering everyone on the front lines to make decisions all at the speed of digital. The transformation starts with you. It's time to lead the way it's time for Thought leaders. >> Welcome to "Thought Leaders" a digital event brought to you by ThoughtSpot. My name is Dave Vellante. The purpose of this day is to bring industry leaders and experts together to really try and understand the important issues around digital transformation. We have an amazing lineup of speakers and our goal is to provide you with some best practices that you can bring back and apply to your organization. Look, data is plentiful, but insights are not. ThoughtSpot is disrupting analytics by using search and machine intelligence to simplify data analysis and really empower anyone with fast access to relevant data. But in the last 150 days, we've had more questions than answers. Creating an organization that puts data and insights at their core requires not only modern technology, but leadership, a mindset and a culture that people often refer to as data-driven. What does that mean? How can we equip our teams with data and fast access to quality information that can turn insights into action. And today we're going to hear from experienced leaders who are transforming their organizations with data, insights and creating digital first cultures. But before we introduce our speakers, I'm joined today by two of my co-hosts from ThoughtSpot first chief data strategy officer at the ThoughtSpot is Cindi Howson. Cindi is an analytics and BI expert with 20 plus years experience and the author of "Successful Business Intelligence "Unlock the Value of BI & Big Data." Cindi was previously the lead analyst at Gartner for the data and analytics magic quadrant. And early last year, she joined ThoughtSpot to help CDOs and their teams understand how best to leverage analytics and AI for digital transformation. Cindi, great to see you welcome to the show. >> Thank you, Dave. Nice to join you virtually. >> Now our second cohost and friend of the cube is ThoughtSpot CEO Sudheesh Nair Hello, Sudheesh how are you doing today? >> I'm well Dave, it's good to talk to you again. >> It's great to see you thanks so much for being here. Now Sudheesh please share with us why this discussion is so important to your customers and of course, to our audience and what they're going to learn today. (upbeat music) >> Thanks, Dave. I wish you were there to introduce me into every room and that I walk into because you have such an amazing way of doing it. Makes me feel all so good. Look, since we have all been cooped up in our homes, I know that the vendors like us, we have amped up our sort of effort to reach out to you with invites for events like this. So we are getting very more invites for events like this than ever before. So when we started planning for this, we had three clear goals that we wanted to accomplish. And our first one that when you finish this and walk away, we want to make sure that you don't feel like it was a waste of time. We want to make sure that we value your time and this is going to be useful. Number two, we want to put you in touch with industry leaders and thought leaders, generally good people that you want to hang around with long after this event is over. And number three, as we plan through this, we are living through these difficult times. We want an event to be this event, to be more of an uplifting and inspiring event too. Now, the challenge is how do you do that with the team being change agents because change and as much as we romanticize it, it is not one of those uplifting things that everyone wants to do, or like to do. The way I think of it sort of like a, if you've ever done bungee jumping and it's like standing on the edges waiting to make that one more step, all you have to do is take that one step and gravity will do the rest, but that is the hardest step to take. Change requires a lot of courage. And when we are talking about data and analytics, which is already like such a hard topic, not necessarily an uplifting and positive conversation in most businesses, it is somewhat scary. Change becomes all the more difficult. Ultimately change requires courage. Courage to first of all challenge the status quo. People sometimes are afraid to challenge the status quo because they are thinking that maybe I don't have the power to make the change that the company needs. Sometimes they feel like I don't have the skills. Sometimes they may feel that I'm probably not the right person do it. Or sometimes the lack of courage manifest itself as the inability to sort of break the silos that are formed within the organizations, when it comes to data and insights that you talked about. There are people in the company who are going to hog the data because they know how to manage the data, how to inquire and extract. They know how to speak data. They have the skills to do that. But they are not the group of people who have sort of the knowledge, the experience of the business to ask the right questions off the data. So there is the silo of people with the answers, and there is a silo of people with the questions. And there is gap. This sort of silos are standing in the way of making that necessary change that we all know the business needs. And the last change to sort of bring an external force sometimes. It could be a tool. It could be a platform, it could be a person, it could be a process, but sometimes no matter how big the company is or how small the company is, you may need to bring some external stimuli to start the domino of the positive changes that are necessary. The group of people that we are brought in, the four people, including Cindi, that you will hear from today are really good at practically telling you how to make that step, how to step off that edge, how to dress the rope, that you will be safe and you're going to have fun. You will have that exhilarating feeling of jumping, for a bungee jump. All four of them are exceptional, but my honor is to introduce Michelle and she's our first speaker. Michelle, I am very happy after watching her presentation and reading our bio, that there are no country vital worldwide competition for cool patterns, because she will beat all of us because when her children were small, they were probably into Harry Potter and Disney. She was managing a business and leading change there. And then as her kids grew up and got to that age where they like football and NFL, guess what? She's the CIO of NFL. What a cool mom? I am extremely excited to see what she's going to talk about. I've seen the slides, tons of amazing pictures. I'm looking to see the context behind it. I'm very thrilled to make the acquaintance of Michelle and looking forward to her talk next. Welcome Michelle, it's over to you. (upbeat music) >> I'm delighted to be with you all today to talk about thought leadership. And I'm so excited that you asked me to join you because today I get to be a quarterback. I always wanted to be one. And I thought this is about as close as I'm ever going to get. So I want to talk to you about quarterbacking, our digital revolution using insights data. And of course, as you said, leadership, first a little bit about myself, a little background, as I said, I always wanted to play football. And this is something that I wanted to do since I was a child. But when I grew up, girls didn't get to play football. I'm so happy that that's changing and girls are now doing all kinds of things that they didn't get to do before. Just this past weekend on an NFL field, we had a female coach on two sidelines and a female official on the field. I'm a lifelong fan and student of the game of football. I grew up in the South. You can tell from the accent. And in the South football is like a religion and you pick sides. I chose Auburn university working in the athletic department. So I'm Testament to you can start the journey can be long. It took me many, many years to make it into professional sports. I graduated in 1987 and my little brother, well, not actually not so little. He played offensive line for the Alabama Crimson Tide. And for those of you who know SCC football, you know this is a really big rivalry. And when you choose sides, your family is divided. So it's kind of fun for me to always tell the story that my dad knew his kid would make it to the NFL. He just bet on the wrong one. My career has been about bringing people together for memorable moments at some of America's most iconic brands, delivering memories and amazing experiences that delight from Universal Studios, Disney to my current position as CIO of the NFL. In this job I'm very privileged to have the opportunity to work with the team that gets to bring America's game to millions of people around the world. Often I'm asked to talk about how to create amazing experiences for fans, guests, or customers. But today I really wanted to focus on something different and talk to you about being behind the scenes and backstage because behind every event, every game, every awesome moment is execution, precise, repeatable execution. And most of my career has been behind the scenes doing just that assembling teams to execute these plans. And the key way that companies operate at these exceptional levels is making good decisions, the right decisions at the right time and based upon data so that you can translate the data into intelligence and be a data-driven culture. Using data and intelligence is an important way that world-class companies do differentiate themselves. And it's the lifeblood of collaboration and innovation. Teams that are working on delivering these kinds of world casts experiences are often seeking out and leveraging next-generation technologies and finding new ways to work. I've been fortunate to work across three decades of emerging experiences, which each required emerging technologies to execute a little bit first about Disney in the 90s, I was at Disney leading a project called destination Disney, which it's a data project. It was a data project, but it was CRM before CRM was even cool. And then certainly before anything like a data-driven culture was ever brought up, but way back then we were creating a digital backbone that enabled many technologies for the things that you see today, like the magic band, Disney's magical express. My career at Disney began in finance, but Disney was very good about rotating you around. And it was during one of these rotations that I became very passionate about data. I kind of became a pain in the butt to the IT team asking for data more and more data. And I learned that all of that valuable data was locked up in our systems. All of our point of sales systems, our reservation systems, our operation systems. And so I became a shadow IT person in marketing, ultimately leading to moving into IT. And I haven't looked back since. In the early two thousands, I was at universal studios theme park as their CIO preparing for and launching "The Wizarding World of Harry Potter" bringing one of history's most memorable characters to life required many new technologies and a lot of data. Our data and technologies were embedded into the rides and attractions. I mean, how do you really think a wan selects you at a wan shop. As today at the NFL? I am constantly challenged to do leading edge technologies, using things like sensors, AI, machine learning, and all new communication strategies and using data to drive everything from player performance, contracts, to where we build new stadiums and hold events with this year being the most challenging yet rewarding year in my career at the NFL. In the middle of a global pandemic, the way we are executing on our season is leveraging data from contract tracing devices joined with testing data, talk about data, actually enabling your business without it w wouldn't be having a season right now. I'm also on the board of directors of two public companies where data and collaboration are paramount. First RingCentral, it's a cloud based unified communications platform and collaboration with video message and phone all in one solution in the cloud and Quotient technologies whose product is actually data. The tagline at Quotient is the result in knowing I think that's really important because not all of us are data companies where your product is actually data, but we should operate more like your product is data. I'd also like to talk to you about four areas of things to think about as thought leaders in your companies. First just hit on it is change how to be a champion and a driver of change. Second, how do you use data to drive performance for your company and measure performance of your company? Third, how companies now require intense collaboration to operate. And finally, how much of this is accomplished through solid data driven decisions. First let's hit on change. I mean, it's evident today more than ever, that we are in an environment of extreme change. I mean, we've all been at this for years and as technologists we've known it, believed it, lived it and thankfully for the most part, knock on what we were prepared for it. But this year everyone's cheese was moved. All the people in the back rooms, IT, data architects and others were suddenly called to the forefront because a global pandemic has turned out to be the thing that is driving intense change in how people work and analyze their business. On March 13th, we closed our office at the NFL in the middle of preparing for one of our biggest events, our kickoff event, the 2020 draft. We went from planning a large event in Las Vegas under the bright lights, red carpet stage to smaller events in club facilities. And then ultimately to one where everyone coaches GM's prospects and even our commissioner were at home in their basements. And we only had a few weeks to figure it out. I found myself for the first time being in the live broadcast event space, talking about bungee jumping. This is really what it felt like. It was one in which no one felt comfortable because it had not been done before. But leading through this, I stepped up, but it was very scary. It was certainly very risky, but it ended up being all so rewarding when we did it. And as a result of this, some things will change forever. Second, managing performance. I mean, data should inform how you're doing and how to get your company to perform at it's level. Highest level. As an example, the NFL has always measured performance, obviously, and it is one of the purest examples of how performance directly impacts outcome. I mean, you can see performance on the field. You can see points being scored in stats, and you immediately know that impact those with the best stats usually when the games. The NFL has always recorded stats since the beginning of time here at the NFL a little this year is our 101 year and athletes ultimate success as a player has also always been greatly impacted by his stats. But what has changed for us is both how much more we can measure and the immediacy with which it can be measured. And I'm sure in your business it's the same. The amount of data you must have has got to have quadrupled and how fast you need it and how quickly you need to analyze it is so important. And it's very important to break the silos between the keys, to the data and the use of the data. Our next generation stats platform is taking data to a next level. It's powered by Amazon web services. And we gathered this data real-time from sensors that are on players' bodies. We gather it in real time, analyze it, display it online and on broadcast. And of course it's used to prepare week to week in addition to what is a normal coaching plan would be. We can now analyze, visualize route patterns, speed match-ups, et cetera. So much faster than ever before. We're continuing to roll out sensors too that will gather more and more information about a player's performance as it relates to their health and safety. The third trend is really, I think it's a big part of what we're feeling today and that is intense collaboration. And just for sort of historical purposes, it's important to think about for those of you that are IT professionals and developers, more than 10 years ago, agile practices began sweeping companies where small teams would work together rapidly in a very flexible, adaptive, and innovative way. And it proved to be transformational. However, today, of course, that is no longer just small teams, the next big wave of change. And we've seen it through this pandemic is that it's the whole enterprise that must collaborate and be agile. If I look back on my career, when I was at Disney, we owned everything 100%. We made a decision, we implemented it. We were a collaborative culture, but it was much easier to push change because you own the whole decision. If there was buy-in from the top down, you've got the people from the bottom up to do it and you executed. At Universal we were a joint venture. Our attractions and entertainment was licensed. Our hotels were owned and managed by other third parties. So influence and collaboration and how to share across companies became very important. And now here I am at the NFL and even the bigger ecosystem, we have 32 clubs that are all separate businesses. 31 different stadiums that are owned by a variety of people. We have licensees, we have sponsors, we have broadcast partners. So it seems that as my career has evolved, centralized control has gotten less and less and has been replaced by intense collaboration, not only within your own company, but across companies. The ability to work in a collaborative way across businesses and even other companies that has been a big key to my success in my career. I believe this whole vertical integration and big top-down decision-making is going by the wayside in favor of ecosystems that require cooperation yet competition to co-exist. I mean, the NFL is a great example of what we call co-op petition, which is cooperation and competition. We're in competition with each other, but we cooperate to make the company the best it can be. And at the heart of these items really are data driven decisions and culture. Data on its own isn't good enough. You must be able to turn it to insights. Partnerships between technology teams who usually hold the keys to the raw data and business units who have the knowledge to build the right decision models is key. If you're not already involved in this linkage, you should be. Data mining isn't new for sure. The availability of data is quadrupling and it's everywhere. How do you know what to even look at? How do you know where to begin? How do you know what questions to ask it's by using the tools that are available for visualization and analytics and knitting together strategies of the company. So it begins with first of all, making sure you do understand the strategy of the company. So in closing, just to wrap up a bit, many of you joined today, looking for thought leadership on how to be a change agent, a change champion, and how to lead through transformation. Some final thoughts are be brave and drive. Don't do the ride along program. It's very important to drive. Driving can be high risk, but it's also high reward. Embracing the uncertainty of what will happen is how you become brave. Get more and more comfortable with uncertainty, be calm and let data be your map on your journey. Thanks. >> Michelle, tank you so much. So you and I share a love of data and a love of football. You said you want to be the quarterback. I'm more an old line person. (Michelle and Cindi laughing) >> Well, then I can do my job without you. >> Great. And I'm getting the feeling now, Sudheesh is talking about bungee jumping. My vote is when we're past this pandemic, we both take them to the Delaware water gap and we do the cliff jumping. >> That sounds good, I'll watch. >> Yeah, you'll watch, okay. So Michelle, you have so many stakeholders when you're trying to prioritize the different voices. You have the players, you have the owners, you have the league, as you mentioned, the broadcasters, your partners here and football mamas like myself. How do you prioritize when there's so many different stakeholders that you need to satisfy? >> I think balancing across stakeholders starts with, aligning on a mission. And if you spend a lot of time understanding where everyone's coming from, and you can find the common thread that ties them all together, you sort of do get them to naturally prioritize their work. And I think that's very important. So for us, at the NFL and even at Disney, it was our core values and our core purpose, is so well known and when anything challenges that we're able to sort of lay that out. But as a change agent, you have to be very empathetic. And I would say empathy is probably your strongest skill if you're a change agent. And that means listening to every single stakeholder, even when they're yelling at you, even when they're telling you your technology doesn't work and you know that it's user error, or even when someone is just emotional about what's happening to them and that they're not comfortable with it. So I think being empathetic and having a mission and understanding it is sort of how I prioritize and balance. >> Yeah, empathy, a very popular word this year. I can imagine those coaches and owners yelling. So, thank you for your leadership here. So Michelle, I look forward to discussing this more with our other customers and disruptors joining us in a little bit. (upbeat music) So we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl what went wrong? 1986, as the reactors were melting down, they had the data to say, this is going to be catastrophic. And yet the culture said, "no, we're perfect, hide it. "Don't dare tell anyone." Which meant they went ahead and had celebrations in Kiev. Even though that increased the exposure, the additional thousands getting cancer and 20,000 years before the ground around there can even be inhabited again, this is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with. And this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So I'll talk about culture and technology. Is it really two sides of the same coin, real-world impacts and then some best practices you can use to and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently a CDO said to me, "Cindi, I actually think this is two sides "of the same coin. "One reflects the other." What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s BI and reporting largely parametrized reports, on premises data, warehouses, or not even that operational reports at best one enterprise data warehouse, very slow moving and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudheesh referred to, or is there also a culture of fear, afraid of failure, resistance to change complacency. And sometimes that complacency it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, no we're measured on least cost to serve. So politics and distrust, whether it's between business and IT or individual stakeholders is the norm. So data is hoarded. Let's contrast that with a leader, a data and analytics leader, what is their technology look like? Augmented analytics search and AI driven insights, not on premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data Lake and in a data warehouse, a logical data warehouse. The collaboration is being a newer methods, whether it's Slack or teams allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL or best serving your customers. It's innovative and collaborative. There's none of this. Oh, well, I didn't invent that. I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast, and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized. And democratized, not just for power users or analysts, but really at the point of impact what we like to call the new decision-makers or really the frontline workers. So Harvard business review partnered with us to develop this study to say, just how important is this? We've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines? Whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor. Everyone said that if our 87% said, they would be more successful if frontline workers were empowered with data driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality, only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture in technology. How did we get here? It's because state-of-the-art keeps changing. So the first-generation BI and analytics platforms were deployed on premises on small datasets, really just taking data out of ERP systems that were also on premises. And state-of-the-art was maybe getting a management report, an operational report. Over time visual-based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations with the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state of the art though, Gartner calls it augmented analytics at ThoughtSpot, we call it search and AI driven analytics. And this was pioneered for large scale datasets, whether it's on premises or leveraging the cloud data warehouses. And I think this is an important point. Oftentimes you, the data and analytics leaders will look at these two components separately, but you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like. Instead of somebody hard coding, a report it's typing in search keywords and very robust keywords contains rank top bottom, getting to a visual visualization that then can be pinned to an existing Pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision maker, the business user, the non analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You use to be able to create an investment place a bet for maybe 10 years, a few years ago, that time horizon was five years, now it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse and pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI driven insights. Competitors have followed suit, but be careful if you look at products like power BI or SAP analytics cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift, or Azure synapse or Google big query, they do not. They require you to move it into a smaller in memory engine. So it's important how well these new products inter operate. the pace of change, its acceleration Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI. And that is roughly three times the prediction they had just a couple years ago. So let's talk about the real world impact of culture. And if you read any of my books or used any of the maturity models out there, whether the Gartner IT score that I worked on, or the data warehousing Institute also has the money surety model. We talk about these five pillars to really become data-driven. As Michelle, I spoke about it's focusing on the business outcomes, leveraging all the data, including new data sources, it's the talent, the people, the technology, and also the processes. And often when I would talk about the people and the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for Thought leaders, you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven it's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years. But look at what happened in the face of negative news with data, it said, "hey, we're not doing good cross selling, "customers do not have both a checking account "and a credit card and a savings account and a mortgage." They opened fake accounts facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture, and they're trying to fix this. But even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples, Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant diabetes, you know this brand. And at the start of COVID when they knew their business would be slowing down, because hospitals would only be able to take care of COVID patients. They took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers. And even though the U.S federal government said, "well, you can't turn them off. They said, "we'll extend that even beyond "the mandated guidelines." And facing a slow down in the business because of the tough economy, they said, you know what? "We will spend the time up skilling our people, "giving them the time to learn more "about the future of work, the skills and data "and analytics," for 20,000 of their employees, rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions, bring in a change agent, identify the relevance, or I like to call it WIFM and organize for collaboration. So the CDO, whatever your title is, chief analytics officer, chief digital officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe, you have the CDO of Just Eat a takeout food delivery organization coming from the airline industry or in Australia, National Australian bank, taking a CDO within the same sector from TD bank going to NAB. So these change agents come in disrupt. It's a hard job. As one of you said to me, it often feels like Sisyphus. I make one step forward and I get knocked down again. I get pushed back. It is not for the faint of heart, but it's the most important part of your job. The other thing I'll talk about is WIFM. What is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the frontline, as well as those analysts, as well as the executives. So if we're talking about players in the NFL, they want to perform better and they want to stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay we could say commissions, but it's really helping people have their dreams come true, whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s for the teachers, teachers, you ask them about data. They'll say we don't, we don't need that. I care about the student. So if you can use data to help a student perform better, that is WIFM. And sometimes we spend so much time talking the technology, we forget what is the value we're trying to deliver with it. And we forget the impact on the people that it does require change. In fact, the Harvard business review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology, but also being empowered to act on those data-driven insights. The third point organize for collaboration. This does require diversity of thought, but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI competency center was considered state-of-the-art. Now for the biggest impact what I recommend is that you have a federated model centralized for economies of scale. That could be the common data, but then in bed, these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible, but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead an exciting time, because data is helping organizations better navigate a tough economy, lock in the customer loyalty. And I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thought Leaders. And next I'm pleased to introduce our first change agent, Tom Mazzaferro chief data officer of Western union. And before joining Western union, Tom made his Mark at HSBC and JPMorgan Chase spearheading digital innovation in technology, operations, risk compliance, and retail banking. Tom, thank you so much for joining us today. (upbeat music) >> Very happy to be here and looking forward to talking to all of you today. So as we look to move organizations to a data-driven, capability into the future, there is a lot that needs to be done on the data side, but also how does data connect and enable different business teams and technology teams into the future. As you look across, our data ecosystems and our platforms and how we modernize that to the cloud in the future, it all needs to basically work together, right? To really be able to drive and over the shift from a data standpoint, into the future, that includes being able to have the right information with the right quality of data, at the right time to drive informed business decisions, to drive the business forward. As part of that, we actually have partnered with ThoughtSpot, to actually bring in the technology to help us drive that as part of that partnership. And it's how we've looked to integrate it into our overall business as a whole we've looked at how do we make sure that our business and our professional lives right, are enabled in the same ways as our personal lives. So for example, in your personal lives, when you want to go and find something out, what do you do? You go onto google.com or you go on to Bing we go onto Yahoo and you search for what you want search to find and answer. ThoughtSpot for us as the same thing, but in the business world. So using ThoughtSpot and other AI capability it's allowed us to actually, enable our overall business teams in our company to actually have our information at our fingertips. So rather than having to go and talk to someone or an engineer to go pull information or pull data, we actually can have the end-users or the business executives, right. Search for what they need, what they want at the exact time that action need it to go and drive the business forward. This is truly one of those transformational things that we've put in place. On top of that, we are on the journey to modernize our larger ecosystem as a whole. That includes modernizing our underlying data warehouses, our technology, or our Eloqua environments. And as we move that, we've actually picked two of our cloud providers going to AWS and GCP. We've also adopted Snowflake to really drive and to organize our information and our data then drive these new solutions and capabilities forward. So they portion of us though is culture. So how do we engage with the business teams and bring the IT teams together to really drive these holistic end to end solutions and capabilities to really support the actual business into the future? That's one of the keys here, as we look to modernize and to really enhance our organizations to become data-driven, this is the key. If you can really start to provide answers to business questions before they're even being asked and to predict based upon different economic trends or different trends in your business, what does this is maybe be made and actually provide those answers to the business teams before they're even asking for it, that is really becoming a data-driven organization. And as part of that, it's really then enables the business to act quickly and take advantage of opportunities as they come in based upon, industries based upon markets, based upon products, solutions, or partnerships into the future. These are really some of the keys that become crucial as you move forward, right, into this new age, especially with COVID. With COVID now taking place across the world, right? Many of these markets, many of these digital transformations are accelerating and are changing rapidly to accommodate and to support customers in these very difficult times, as part of that, you need to make sure you have the right underlying foundation ecosystems and solutions to really drive those capabilities and those solutions forward. As we go through this journey, both of my career, but also each of your careers into the future, right? It also needs to evolve, right? Technology has changed so drastically in the last 10 years, and that change is only accelerating. So as part of that, you have to make sure that you stay up to speed, up to date with new technology changes both on the platform standpoint tools, but also what do our customers want? What do our customers need and how do we then service them with our information, with our data, with our platform and with our products and our services to meet those needs and to really support and service those customers into the future. This is all around becoming a more data organization such as how do you use your data to support the current business lines, but how do you actually use your information, your data to actually put a better support your customers, better support your business, better support your employees, your operations teams, and so forth, and really creating that full integration in that ecosystem is really when you start to get large dividends from this investments into the future. But that being said, hope you enjoy the segment on how to become and how to drive it data driven organization. And, looking forward to talking to you again soon. Thank you. >> Tom that was great thanks so much. Now I'm going to have to brag on you for a second as a change agent you've come in disrupted and how long have you been at Western union? >> Only nine months, so just started this year, but, doing some great opportunities and great changes. And we have a lot more to go, but, we're really driving things forward in partnership with our business teams and our colleagues to support those customers going forward. >> Tom, thank you so much. That was wonderful. And now I'm excited to introduce you to Gustavo Canton, a change agent that I've had the pleasure of working with meeting in Europe, and he is a serial change agent, most recently with Schneider electric, but even going back to Sam's clubs, Gustavo welcome. (upbeat music) >> So, hey everyone, my name is Gustavo Canton and thank you so much, Cindi, for the intro, as you mentioned, doing transformations is high effort, high reward situation. I have empowered many transformations and I have led many transformations. And what I can tell you is that it's really hard to predict the future, but if you have a North star and where you're going, the one thing that I want you to take away from this discussion today is that you need to be bold to evolve. And so in today, I'm going to be talking about culture and data, and I'm going to break this down in four areas. How do we get started barriers or opportunities as I see it, the value of AI, and also, how do you communicate, especially now in the workforce of today with so many different generations, you need to make sure that you are communicating in ways that are non-traditional sometimes. And so how do we get started? So I think the answer to that is you have to start for you yourself as a leader and stay tuned. And by that, I mean, you need to understand not only what is happening in your function or your field, but you have to be varying into what is happening in society, socioeconomically speaking wellbeing. The common example is a great example. And for me personally, it's an opportunity because the one core value that I have is well-being, I believe that for human potential, for customers and communities to grow wellbeing should be at the center of every decision. And as somebody mentioned is great to be, stay in tune and have the skillset and the courage. But for me personally, to be honest, to have this courage is not about not being afraid. You're always afraid when you're making big changes when you're swimming upstream, but what gives me the courage is the empathy part. Like I think empathy is a huge component because every time I go into an organization or a function, I try to listen very attentively to the needs of the business and what the leaders are trying to do. What I do it thinking about the mission of how do I make change for the bigger, workforce? for the bigger good. Despite this fact that this might have a perhaps implication on my own self-interest in my career, right? Because you have to have that courage sometimes to make choices that I know we'll see in politically speaking, what are the right thing to do? And you have to push through it. And you have to push through it. So the bottom line for me is that I don't think they're transforming fast enough. And the reality is I speak with a lot of leaders and we have seen stories in the past. And what they show is that if you look at the four main barriers that are basically keeping us behind budget, inability to act cultural issues, politics, and lack of alignment, those are the top four. But the interesting thing is that as Cindi has mentioned, these topics culture is actually gaining, gaining more and more traction. And in 2018, there was a story from HBR and it was about 45%. I believe today it's about 55%, 60% of respondents say that this is the main area that we need to focus on. So again, for all those leaders and all the executives who understand and are aware that we need to transform, commit to the transformation and set a state, deadline to say, "hey, in two years, we're going to make this happen. "What do we need to do to empower and enable "this change engines to make it happen?" You need to make the tough choices. And so to me, when I speak about being bold is about making the right choices now. So I'll give you samples of some of the roadblocks that I went through as I think transformation most recently, as Cindi mentioned in Schneider. There are three main areas, legacy mindset. And what that means is that we've been doing this in a specific way for a long time and here is how we have been successful what was working the past is not going to work now. The opportunity there is that there is a lot of leaders who have a digital mindset and there're up and coming leaders that are not yet fully developed. We need to mentor those leaders and take bets on some of these talent, including young talent. We cannot be thinking in the past and just wait for people, three to five years for them to develop because the world is going to in a way that is super fast. The second area, and this is specifically to implementation of AI is very interesting to me because just example that I have with ThoughtSpot, right, we went to implementation and a lot of the way is the IT team function of the leaders look at technology, they look at it from the prism of the prior all success criteria for the traditional Bi's. And that's not going to work. Again the opportunity here is that you need to really find what successful look like. In my case, I want the user experience of our workforce to be the same as user experience you have at home is a very simple concept. And so we need to think about how do we gain the user experience with this augmented analytics tools and then work backwards to have the right talent processes and technology to enable that. And finally, with COVID a lot of pressuring organizations, and companies to do more with less. And the solution that most leaders I see are taking is to just minimize costs, sometimes in cut budget, we have to do the opposite. We have to actually invest some growth areas, but do it by business question. Don't do it by function. If you actually invest in these kind of solutions, if you actually invest on developing your talent, your leadership to see more digitally, if you actually invest on fixing your data platform, it's not just an incremental cost. It's actually this investment is going to offset all those hidden costs and inefficiencies that you have on your system, because people are doing a lot of work and working very hard, but it's not efficiency, and it's not working in the way that you might want to work. So there is a lot of opportunity there. And you just to put into some perspective, there have studies in the past about, how do we kind of measure the impact of data. And obviously this is going to vary by your organization maturity, is going to, there's going to be a lot of factors. I've been in companies who have very clean, good data to work with. And I think with companies that we have to start basically from scratch. So it all depends on your maturity level, but in this study, what I think is interesting is they try to put attack line or attack price to what is the cost of incomplete data. So in this case, it's about 10 times as much to complete a unit of work when you have data that is flawed as opposed to have perfect data. So let me put that just in perspective, just as an example, right? Imagine you are trying to do something and you have to do 100 things in a project, and each time you do something, it's going to cost you a dollar. So if you have perfect data, the total cost of that project might be $100. But now let's say you have any percent perfect data and 20% flawed data by using this assumption that flawed data is 10 times as costly as perfect data. Your total costs now becomes $280 as opposed to $100. This is just for you to really think about as a CIO CTO, CHRO CEO, are we really paying attention and really closing the gaps that we have on our data infrastructure. If we don't do that, it's hard sometimes to see the snowball effect or to measure the overall impact. But as you can tell the price that goes up very, very quickly. So now, if I were to say, how do I communicate this? Or how do I break through some of these challenges or some of these various, right. I think the key is I am in analytics. I know statistics obviously, and love modeling and data and optimization theory and all that stuff. That's what I came to analytics. But now as a leader and as a change agent, I need to speak about value. And in this case, for example, for Schneider, there was this tagline called free up your energy. So the number one thing that they were asking from the analytics team was actually efficiency, which to me was very interesting. But once I understood that I understood what kind of language to use, how to connect it to the overall strategy and basically how to bring in the, the right leaders, because you need to focus on the leaders that you're going to make the most progress. Again, low effort, high value. You need to make sure you centralize all the data as you can. You need to bring in some kind of augmented analytics solution. And finally you need to make it super simple for the, in this case, I was working with the HR teams in other areas, so they can have access to one portal. They don't have to be confused in looking for 10 different places to find information. I think if you can actually have those four foundational pillars, obviously under the guise of having a data-driven culture, that's when you can actually make the impact. So in our case, it was about three years total transformation, but it was two years for this component of augmented analytics. It took about two years to talk to IT get leadership support, find the budgeting, get everybody on board, make sure the safe criteria was correct. And we call this initiative, the people analytics portal, it was actually launched in July of this year. And we were very excited and the audience was very excited to do this. In this case, we did our pilot in North America for many, many manufacturers. But one thing that is really important is as you bring along your audience on this, you're going from Excel, in some cases or Tableau to other tools like, ThoughtSpot, you need to really explain them what is the difference and how these tools can truly replace, some of the spreadsheets or some of the views that you might have on these other kind of tools. Again, Tableau, I think it's a really good tool. There are other many tools that you might have in your toolkit. But in my case, personally, I feel that you need to have one portal going back to Cindi's point. I really truly enable the end user. And I feel that this is the right solution for us, right? And I will show you some of the findings that we had in the pilot in the last two months. So this was a huge victory, and I will tell you why, because it took a lot of effort for us to get to the station. Like I said, it's been years for us to kind of lay the foundation, get the leadership, and shaping culture so people can understand why you truly need to invest on (indistinct) analytics. And so what I'm showing here is an example of how do we use basically, a tool to capture in video the qualitative findings that we had, plus the quantitative insights that we have. So in this case, our preliminary results based on our ambition for three main metrics, hours saved user experience and adoption. So for hours saved or a mission was to have 10 hours per week per employee save on average user experience, or ambition was 4.5. And adoption, 80%. In just two months, two months and a half of the pilot, we were able to achieve five hours per week per employee savings. Our user experience for 4.3 out of five and adoption of 60%. Really, really amazing work. But again, it takes a lot of collaboration for us to get to the stage from IT, legal, communications, obviously the operations teams and the users in HR safety and other areas that might be, basically stakeholders in this whole process. So just to summarize this kind of effort takes a lot of energy. You are a change agent. You need to have a courage to make the decision and understand that I feel that in this day and age, with all this disruption happening, we don't have a choice. We have to take the risk, right? And in this case, I feel a lot of satisfaction in how we were able to gain all these very source for this organization. And that gave me the confidence to know that the work has been done and we are now in a different stage for the organization. And so for me, it to say, thank you for everybody who has believed, obviously in our vision, everybody who has believe in the word that we were trying to do and to make the life of four workforce or customers or in community better. As you can tell, there is a lot of effort. There is a lot of collaboration that is needed to do something like this. In the end, I feel very satisfied. With the accomplishments of this transformation, and I just want to tell for you, if you are going right now in a moment that you feel that you have to swim upstream what would mentors, what would people in this industry that can help you out and guide you on this kind of a transformation is not easy to do is high effort, but is well worth it. And with that said, I hope you are well, and it's been a pleasure talking to you. Talk to you soon, take care. >> Thank you, Gustavo, that was amazing. All right, let's go to the panel. (air whooshing) >> Okay, now we're going to go into the panel and bring Cindi, Michelle, Tom, and Gustavo back and have an open discussion. And I think we can all agree how valuable it is to hear from practitioners. And I want to thank the panel for sharing their knowledge with the community. And one common challenge that I heard you all talk about was bringing your leadership and your teams along on the journey with you. We talk about this all the time, and it is critical to have support from the top. Why? Because it directs the middle and then it enables bottoms up innovation effects from the cultural transformation that you guys all talked about. It seems like another common theme we heard is that you all prioritize database decision-making in your organizations and you combine two of your most valuable assets to do that and create leverage, employees on the front lines. And of course the data. And as you rightly pointed out, Tom, the pandemic has accelerated the need for really leaning into this. The old saying, if it ain't broke don't fix it. Well COVID is broken everything. And it's great to hear from our experts, how to move forward. So let's get right into it. So Gustavo, let's start with you if I'm an aspiring change agent and let's say I'm a budding data leader. What do I need to start doing? What habits do I need to create for long lasting success? >> I think curiosity is very important. You need to be, like I say, in tune to what is happening, not only in your specific field, like I have a passion for analytics, I can do this for 50 years plus, but I think you need to understand wellbeing other areas across not only a specific business, as you know I come from, Sam's club Walmart, retail, I mean energy management technology. So you have to try to push yourself and basically go out of your comfort zone. I mean, if you are staying in your comfort zone and you want to use lean continuous improvement, that's just going to take you so far. What you have to do is, and that's what I try to do is I try to go into areas, businesses, and transformation that make me stretch and develop as a leader. That's what I'm looking to do so I can help transform the functions organizations and do the change management, change of mindset required for these kinds of efforts. >> Michelle, you're at the intersection of tech and sports and what a great combination, but they're both typically male oriented fields. I mean, we've talked a little bit about how that's changing, but two questions. Tell us how you found your voice and talk about why diversity matters so much more than ever now. >> No, I found my voice really as a young girl, and I think I had such amazing support from men in my life. And I think the support and sponsorship as well as sort of mentorship along the way, I've had amazing male mentors who have helped me understand that my voice is just as important as anyone else's. I mean, I have often heard, and I think it's been written about that a woman has to believe they'll 100% master topic before they'll talk about it where a man can feel much less mastery and go on and on. So I was that way as well. And I learned just by watching and being open, to have my voice. And honestly at times demand a seat at the table, which can be very uncomfortable. And you really do need those types of, support networks within an organization. And diversity of course is important and it has always been. But I think if anything, we're seeing in this country right now is that diversity among all types of categories is front and center. And we're realizing that we don't all think alike. We've always known this, but we're now talking about things that we never really talked about before. And we can't let this moment go unchecked and on, and not change how we operate. So having diverse voices within your company and in the field of tech and sports, I am often the first and only I'm was the first, CIO at the NFL, the first female senior executive. It was fun to be the first, but it's also, very challenging. And my responsibility is to just make sure that, I don't leave anyone behind and make sure that I leave it good for the next generation. >> Well, thank you for that. That is inspiring. And Cindi, you love data and the data's pretty clear that diversity is a good business, but I wonder if you can add your perspectives to this conversation? >> Yeah, so Michelle has a new fan here because she has found her voice. I'm still working on finding mine. And it's interesting because I was raised by my dad, a single dad. So he did teach me how to work in a predominantly male environment, but why I think diversity matters more now than ever before. And this is by gender, by race, by age, by just different ways of working in thinking is because as we automate things with AI, if we do not have diverse teams looking at the data and the models and how they're applied, we risk having bias at scale. So this is why I think I don't care what type of minority you are finding your voice, having a seat at the table and just believing in the impact of your work has never been more important. And as Michelle said more possible. >> Great perspectives, thank you. Tom I want to go to you. I mean, I feel like everybody in our businesses in some way, shape or form become a COVID expert, but what's been the impact of the pandemic on your organization's digital transformation plans? >> We've seen a massive growth actually in a digital business over the last, 12 months, really, even in celebration, right? Once COVID hit, we really saw that in the 200 countries and territories that we operate in today and service our customers, today, that there's been a huge need, right? To send money, to support family, to support, friends and support loved ones across the world. And as part of that we are very, honored to get to support those customers that we, across all the centers today. But as part of that acceleration we need to make sure that we had the right architecture and the right platforms to basically scale, right, to basically support and provide the right kind of security for our customers going forward. So as part of that, we did do some pivots and we did accelerate some of our plans on digital to help support that overall growth coming in and to support our customers going forward, because there were these times during this pandemic, right? This is the most important time. And we need to support those that we love and those that we care about and doing that it's one of those ways is actually by sending money to them, support them financially. And that's where, really our part of that our services come into play that we really support those families. So it was really a great opportunity for us to really support and really bring some of our products to this level and supporting our business going forward. >> Awesome, thank you. Now I want to come back to Gustavo, Tom I'd love for you to chime in too. Did you guys ever think like you were, you were pushing the envelope too much in doing things with data or the technology that was just maybe too bold, maybe you felt like at some point it was failing or you're pushing your people too hard. Can you share that experience and how you got through it? >> Yeah, the way I look at it is, again, whenever I go to an organization, I ask the question, hey, how fast you would like transform. And, based on the agreements from the leadership and the vision that we want to take place, I take decisions. And I collaborate in a specific way now, in the case of COVID, for example, right. It forces us to remove silos and collaborate in a faster way. So to me, it was an opportunity to actually integrate with other areas and drive decisions faster, but make no mistake about it. When you are doing a transformation, you are obviously trying to do things faster than sometimes people are comfortable doing, and you need to be okay with that. Sometimes you need to be okay with tension, or you need to be okay debating points or making repetitive business cases until people connect with the decision because you understand, and you are seeing that, "hey, the CEO is making a one two year, efficiency goal. "The only way for us to really do more with less "is for us to continue this path. "We cannot just stay with the status quo. "We need to find a way to accelerate the transformation." That's the way I see it. >> How about you Tom, we were talking earlier with Sudheesh and Cindi, about that bungee jumping moment. What could you share? >> Yeah, I think you hit upon it, right now, the pace of change with the slowest pace that you see for the rest of your career. So as part of that, right, that's what I tell my team is that you need to be, you need to feel comfortable being uncomfortable. I mean, that we have to be able to basically scale, right, expand and support that the ever-changing needs in the marketplace and industry our customers today, and that pace of change that's happening, right. And what customers are asking for and the competition in the marketplace, it's only going to accelerate. So as part of that, as you look at what, how you're operating today in your current business model, right. Things are only going to get faster. So you have to plan into a line into drive the agile transformation so that you can scale even faster in the future. So as part of that, that's what we're putting in place here, right, is how do we create that underlying framework and foundation that allows the organization to basically continue to scale and evolve into the future? >> Yeah, we're definitely out of our comfort zones, but we're getting comfortable with it. So, Cindi, last question, you've worked with hundreds of organizations, and I got to believe that, some of the advice you gave when you were at Gartner, which is pre COVID, maybe sometimes clients didn't always act on it. They're not on my watch for whatever variety of reasons, but it's being forced on them now. But knowing what you know now that we're all in this isolation economy, how would you say that advice has changed? Has it changed? What's your number one action and recommendation today? >> Yeah, well, first off, Tom just freaked me out. What do you mean? This is the slowest ever even six months ago I was saying the pace of change in data and analytics is frenetic. So, but I think you're right, Tom, the business and the technology together is forcing this change. Now, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, very aware of the power and politics and how to bring people along in a way that they are comfortable. And now I think it's, you know what you can't get comfortable. In fact, we know that the organizations that were already in the cloud have been able to respond and pivot faster. So if you really want to survive as Tom and Gustavo said, get used to being uncomfortable, the power and politics are going to happen. Break the rules, get used to that and be bold. Do not be afraid to tell somebody they're wrong and they're not moving fast enough. I do think you have to do that with empathy, as Michelle said, and Gustavo, I think that's one of the key words today besides the bungee jumping. So I want to know where's the dish going to go bungee jumping. >> Guys fantastic discussion, really. Thanks again to all the panelists and the guests. It was really a pleasure speaking with you today. Really virtually all of the leaders that I've spoken to in the Cube program. Recently, they tell me that the pandemic is accelerating so many things, whether it's new ways to work, we heard about new security models and obviously the need for cloud. I mean, all of these things are driving true enterprise wide digital transformation, not just, as I said before, lip service. Sometimes we minimize the importance and the challenge of building culture and in making this transformation possible. But when it's done, right, the right culture is going to deliver tremendous results. Yeah, what does that mean getting it right? Everybody's trying to get it right. My biggest takeaway today is it means making data part of the DNA of your organization. And that means making it accessible to the people in your organization that are empowered to make decisions, decisions that can drive new revenue, cut costs, speed access to critical care, whatever the mission is of your organization. Data can create insights and informed decisions that drive value. Okay. Let's bring back Sudheesh and wrap things up. Sudheesh, please bring us home. >> Thank you. Thank you, Dave. Thank you, the Cube team, and thank goes to all of our customers and partners who joined us and thanks to all of you for spending the time with us. I want to do three quick things and then close it off. The first thing is I want to summarize the key takeaways that I had from all four of our distinguished speakers. First, Michelle, I will simply put it. She said it really well. That is be brave and drive. Don't go for a drive along. That is such an important point. Oftentimes, you know that I think that you have to do to make the positive change that you want to see happen but you wait for someone else to do it, not just, why not you? Why don't you be the one making that change happen? That's the thing that I've picked up from Michelle's talk. Cindi talked about finding the importance of finding your voice. Taking that chair, whether it's available or not, and making sure that your ideas, your voices are heard, and if it requires some force, then apply that force. Make sure your ideas are heard. Gustavo talked about the importance of building consensus, not going at things all alone sometimes building the importance of building the quorum. And that is critical because if you want the changes to last, you want to make sure that the organization is fully behind it. Tom, instead of a single takeaway, what I was inspired by is the fact that a company that is 170 years old, 170 years old, 200 companies and 200 countries they're operating in. And they were able to make the change that is necessary through this difficult time. So in a matter of months, if they could do it, anyone could. The second thing I want to do is to leave you with a takeaway that is I would like you to go to topspot.com/nfl because our team has made an app for NFL on Snowflake. I think you will find this interesting now that you are inspired and excited because of Michelle's talk. And the last thing is please go to thoughtspot.com/beyond our global user conference is happening in this December. We would love to have you join us. It's again, virtual, you can join from anywhere. We are expecting anywhere from five to 10,000 people, and we would love to have you join and see what we've been up to since last year. We have a lot of amazing things in store for you, our customers, our partners, our collaborators, they will be coming and sharing. We'll be sharing things that we've have been working to release something that will come out next year. And also some of the crazy ideas our engineers have been cooking up. All of those things will be available for you at the Thought Spot Beyond. Thank you. Thank you so much.

(upbeat music) >> Narrator: Live from the Wynn Hotel in Las Vegas, it's theCUBE, covering Magento Imagine 2018. Brought to you by Magento. >> Welcome back to theCUBE's continuing coverage of Magento Imagine 2018 from Las Vegas. I'm Lisa Martin, joined by Anita Andrews, the director of analytical services at Magento. Anita, welcome to theCUBE. >> Hi, Lisa. How are you? (laughs) >> Very good, excited to be here. This is a really interesting topic, commerce. We talk a lot on theCUBE about digital transformation in so many different contexts. But really, it seems that commerce is becoming the center of gravity for digital transformation. Data is everywhere. There's so much opportunity for B to B organizations, B to C organizations, to leverage that data to drive new revenue streams, et cetera. Talk to us about what Magento is doing with respect to BI and how you're enabling your customers to use it to better their businesses. >> Yeah, so, I'm so glad that you sort of asked this question because we're doing a lot of conversations at this Imagine as opposed to previous ones around BI, around analytics, the role of data. And it's because I think we have a conversation and a story to tell around this. It's actually been long in the making. So, what we've learned after working with thousands of clients, from the basics of KPIs and reporting all the way up to machine learning, is that the approach to how do you launch this aspect of the business, really, that powers the entire business, is so important. Because otherwise, you end up with a crazy Christmas tree of solutions and no one really is moving the KPIs of the business forward using data. So, what we are doing is, we've created an infrastructure that allows all kinds of data. Whatever data that you have. It could be in a spreadsheet or it could be an automated feed. To come together into the platform to cleanse it, because everybody has dirty data, cleanse it, sort of model it for your use, and then be able to leverage it for, of course, KPIs reporting, but also run advanced data science on it, and then use that to power the commerce. And not just cross-sales and up-sales on the website, that's a story everybody wants to do and many aren't even doing yet, but also for things like email marketing, for online advertising, for vendor management, for inventory management. I mean, there's so many use cases. So, it's really about bringing the data together into a single place and then using that all throughout the organization. >> So, this is the eighth Magento Imagine. >> Anita: It's my first! (laughs) >> Mine too, ours too, at theCUBE! But you were saying that this is, the topic of business intelligence, is relatively new. Tell us, the role of data, you mentioned a number of use cases and multiple lines of business in an organization that can benefit from this. Why is this something that you think now is becoming so critical when 'big data' as a term has been around for quite some time? >> For a long time, and data has been around for a long term, right, everybody has spreadsheets from years back. I don't think it's that the role of data is becoming more important, per se, but I think that a lot of businesses have tried a lot of things and had sort of spotty successes, so online marketing is a lot better now with data. Right, I mean, absolutely. But this notion that there's these silos across the organization and the whole, I'm sure you guys have talked about this either today or yesterday, the whole customer-centric view that is becoming so vital to the business >> It's essential. online, offline, multi-channel. Well, the only way you do that is if you don't have silos. Right, and so this question of how do we bring all of this together and create the customer-centric view, and, by the way, you know, apply AI to many aspects of the customer experience, it can only happen if we sort of elevate the usage, the consolidation, all of that, and so I think that's a bigger problem. It's easy to kind of have a team work with data on its own. It's much more, it requires a lot more thought to kind of bring it all together and also get going, right? This isn't a a four-year plan to get there. You need to get going soon. >> Exactly, or you risk falling behind and not being able to catch up. So, let's talk about this modern stack. >> Anita: Yeah. >> This modern technology stack to capitalize on the e-commerce opportunities. Give us an example of a B to B organization, what they have existing when Magento comes and how they're able to use your technology across that spectrum of BI. >> Sure, so, most B to B organizations have data. Let's list some common sources of that data, right. So, first of all, they're going to have, most likely, Salesforce or some other sort of CRM database. They're going to have some sort of vendor database, right, either using a third-party tool or something they've home-grown. So often, something they've home-grown. They certainly have online marketing data, they've got transactional data, all of these different things that need to come together. So, in that way, they can leverage the MBI product, Magento Business Intelligence, to bring those data sources in together. Also, they can bring in their spreadsheets or whatever. But you use MBI to bring it together and then there's a level within that stack, the transformation layer, that allows you to sort of edit that data, right. I mean, back to the point of dirty data, edit it so that it's clean. So, you know that, well, in March we were wrongly charging shipping or something like that. Whatever the issues were, cleansing. And then start to report on that within MBI and create whatever sort of analytics you need to. But then you can also incorporate machine learning algorithms to start doing things like predictive analytics. So, start doing this vendor management, et cetera and then use that to, actually, MBI comes with some pre-built B to B dashboards, which is a thing that we just launched in the past year, which is also proving very useful. I mean, businesses have never seen this sort of total view of their customers, their data. And then you take, sort of, some of the learning and some of the information that's in the MBI and then use that to configure personalization Magento 2 commerce or, again, some of these other channels which might be email marketing, which might be, you know, call center scripting. I mean, whatever it is, that's kind of how it comes together. The MBI stack powering Magento 2, whether it's cloud or enterprise, and then other third-party tools that make sense to the customer as well. >> So, the customer has an existing POS system or an ERP system or a web store. Is it a simple integration process? How do they go about integrating that with, especially with, an accent group is coming on later today that has a hundred thousand skews and three thousand products. >> Yeah, so, the aim and the aspiration of MBI is to be able to take any data source, right. So, there's a bunch of data sources for which we have automated integrations. Literally, you put in your credentials and it starts flowing right away. Another option is that you have an API that you can use to import data in, so, if you've got the resources to leverage that, that's an option. Sometimes, if we don't have an automated integration, a lot of third-party data sources now will allow you to put them in a MySQL database or something like that. You can just just connect that directly to MBI, as well. And finally, we're very much looking at, from a product standpoint, how do we leverage the incredible community we have around Magento to develop more integrations, right. Because we cannot keep pace with the thousands and thousands of data sources that are launching every day. So, this community can and they are so close to what customers need to be able to bring in from a data perspective, so, we're also exploring that possibility as well, which would completely change the game. >> Yeah, you've got a very active developer community of, what, three hundred thousand developers? >> Yeah, it's something phenomenal like that. >> Lisa: That is phenomenal. >> Yes. >> When we look at the spectrum of analytics and we get towards the, whichever end it is, the right side, the left side, looking at advanced analytics. >> Anita: Yes. >> Artificial intelligence, for example, can you give us an example of a Magento customer that's being able to utilize artificial intelligence to drive new revenue streams or reduce attrition. Anything that comes to mind that's a really strong hallmark of your capabilities? >> Yeah, so, one of the ones that I love the most is around inventory management. And that applies to B to B and B to C, right. So, one of the things that we're starting to see a lot of traction and results around is advanced analytics and machine learning that's predicting how much inventory you have. So, inventory is money. You don't have enough, you're going to lose your customers. If you have too much, that's dollars sitting on the shelf, right, or accounts payable to your vendors, I mean, whatever it is. So, it is so, traditionally, it's been very hard to predict what you're going to need and when you're going to need it. So, there is now capability within MBI that you can feed into your vendor management or other sorts of merchandising management systems wherein you can sort of say, if you have a two week lead time to be able to get new inventory, then it can predict which of your skews, which of your products, are going to be running out before that two weeks end. And what we've seen with customers that are leveraging that is incredible increase in customer satisfaction rates because that sort of mismatch of, I thought I was going to get this but no, I'm not getting this, is going down. But they're also able to not even have to say it's out of stock on the site, which is a such a disappointing factor. So, improvement in conversion rates and customer satisfaction rates and on the flip side, there's another aspect of that functionality that says, well, do you have more inventory than, let's say, you know, two months' worth? And that two months piece is configurable per business, because if you're an outdoor goods store, two months in March for winter stuff is too late, right? You need to get rid of that now. But at the start of winter, four months might be great. So, all of that is totally configurable to be customized to that business, who knows the particulars of their business so well. And so, what we're seeing there is the, sort of, cost of goods that are being sent into after-market channels or sale or discount channels, is going down dramatically. And that's just a great case that I love because it's applicable, like I said, to B to B and B to C. >> So, on a B to B front, we have a lot of businesses behind us here. >> Anita: Yeah. >> As consumers, we expect to be able to get whatever we want whenever we want. Amazon just announced a hundred million Amazon Prime subscribers >> That's a lot of people. And people will not buy something if it's not available on Amazon Prime. We just think, what? We have to wait a week? >> Must not be a thing. (laughs) >> Exactly, exactly. But also something that the gentleman that was on main stage this morning from Amazon said, that about half of what's purchased on Amazon isn't sold by Amazon. >> Anita: Yeah. >> So, in the consumer space, we have this bar set very, very high. As business buyers, business buyers are consumers in their daily lives, as well. >> Anita: Yeah. I wonder, what are some of the trends that you're seeing on the B to B side that are maybe spilling over or being influenced by the consumer side and how is Magento helping businesses to be able to create these seamless experiences for businesses to transact in a high-velocity, low-touch model? >> Yeah, that's a really good question. You and I were talking before we got started here about how the buyers in a B to B environment, they're not a corporation. They're individuals. They're humans that actually are bringing their B to C personal experiences and expectations into their workplace. I mean, they don't turn into another person, right. They're maybe harder for procurement, you know, channels and all of that, but they're bringing the same expectations into it. So, frankly, you know, while Magento has sort of a B to B focused technology commerce platform, as well, that we've launched and is growing, as does MBI, you know, that will be a growing aspect, a particularization of the Magento platform. On the flip side, what we're also doing is saying they're not different and we're setting high standards for our B to B customers to say, it may be more challenging for you to act like a B to C customer, but that doesn't mean you get to, it may be hard for you to act like a B to C business, but that doesn't mean you get to not act like one, right, because the expectations are there. So, things like, whether it's as simple as what is order management, right, what is order tracking, what are ship and delivery timelines look like? Do I have various payment mechanisms, right? Consumers expect that, right, and those are often geographically dictated. Well, in the business environment, there may be other sort of procurement things to be thoughtful of. So, the conversation we're having, whether it's from a services standpoint or from a technology and product standpoint is have the same standards. And that is, frankly, in the conversations that I have day to day, I get a lot of but buts. You know, but, that's hard for us. Yeah, but so? Right, so let's figure this out. And, of course, you have to prioritize and all of that, you're not going to sort of turn from one end to the other overnight, but really, the message that we are seeing successful B to B customers hear and act upon is meet those consumer expectations and you'll knock it out of the park. >> Lisa: And who doesn't want to do that? >> Right. >> So, let's kind of turn the tides here. Let's look at Magento and how you're using your own technologies. How are you using analytics across that spectrum to really change the entire model? For example, you know, we talked about before we went on, as well, marketing. I'm a marketer. Marketing is a science now because marketers and every line of business has the ability to leverage data to drive many new opportunities. Talk to us about, internally, how you guys are using this spectrum of analytics >> Yeah. to continue to expand in B to B and B to C. >> Yeah, so, I'm going to give you a couple of different use cases, but this will be interesting because we're sort of opening up the kimono here about what goes on, you know, in our offices. So, yesterday, I actually heard our head of development, Ramadass, talk about a use case for using Magento BI within his organization. All of his different many development teams were tracking their tickets and numbers and all of that in various different ways and he sort of came in and said, well, this isn't going to work. I can't measure my organization. And he decided to deploy Magento BI across the whole thing. That wasn't easy, he said it wasn't smooth, but he started with one group who sort of took to it, and then once the benefit started to be seen, started to deploy across all the organization and he said, you know, he had the foresight and patience to stick with it and now he's got, you know, consistent view of what's going on there in the organization. Another angle that we use it from is, for example, with Mangento BI, there's certainly, it's different than implementing Magento Commerce, where, well, maybe it's not that different, but one aspect that I think is different is you do a lot of work to launch Magento Commerce and then, yes, you can expand your use a bit. MBI is pretty quick to get going, but how much you're using it throughout your organization or even within the product takes time. So, we've leveraged our predictive analytics to understand, to track those customer behaviors, and understand, well, when might be a good time to talk to them about, you know, machine learning? When might be a good time to talk to them about, you know, inventory management, whatever those topics are. But we're looking at those customer attributes, how far along are they in MBI, to run our online marketing campaigns, but even our personal marketing campaigns. We're not so big that we can't call up in our own customer success experiences and say, we think you're in a good place where you might want to think about doing this, as well. And then a third place is around customer support, so, a couple years ago, we used the product to figure out how much time were we spending on our customers, right? And there's a notion of a rate per hour. Are we allocating our time properly? It's very easy for the squeaky wheel to get the most attention. Is that the right thing for the business? So, these are the ways that we've used it internally. We're B to B, right? (laughs) >> Right! Would it be fair to say that you're democratizing data within Magento? >> Yes, everybody, I can at least speak to it on the MBI side and I know this is true in development, et cetera, everybody has access to the data. And that's kind of where, watching, you know, an individual contributor take that and run with it and sometimes it's a little bit too eager for me, and then I have to kind of dial it back, and we can't make all those changes today, but it is so impressive to see what they think about asking, what questions they think about asking of the business and that they feel like will solve an actual problem. >> So, kind of allowing innovation. Well, Anita, thank you so much for taking some time >> Yeah, thank you. to stop by theCUBE. We wish you the best of luck in your general session presentation this afternoon and we look forward to hearing from some of your customers and some of your leaders on the program later today. >> Great, thank you, Lisa. >> We want to thank you for watching theCUBE. We are live in Las Vegas at Magento Imagine 2018. Stick around, I'm Lisa Martin. We'll be back with our next guest after a short break. (upbeat music)

>> Announcer: Live, from Las Vegas, it's theCube! Covering NAB 2017. Brought to you by HGST. >> Hey welcome back everybody, Jeff Frick here with theCUBE. We're at NAB 2017, a hundred thousand people. The Las Vegas Convention Center is packed. And it's everything you could ever want to get involved in video and media, and it' pretty crazy exciting. I hope, trying and get the guys from spending all of our budget money next year on new cameras. But, we're excited to have Brian Raleigh on. He's a VP post-production and production business intelligence at ABC Studios. Welcome. >> Thank you, I'm excited to be here, as well. >> Absolutely, so first impressions of the show. You said you haven't been that many times. As you walk around, what strikes you? >> Yeah, this is only my second time here. I will say I've seen plenty of booths that have the words Ingestion, Transcode, Archival, Distribution, there certainly is a lot of distribution out here, the broadcasting convention. >> Jeff: Right. >> Which makes sense. >> But you're involved in that pesky little process between what comes off the camera and what goes out to distribution. >> Yeah, exactly. We're prior to broadcast, right. So my world is really production and post-production, and the production management systems we use within them. >> Right. So love to hear, kind of, how is that world evolved? It used to be you had an artist on a machine, with local files doing the editing and all this stuff, and clearly that world is long, long gone. >> Yeah, most of our production and post-production workflow is in the cloud. >> Jeff: Right. >> Or however you want to call it. And very recently, what we've done, is we've tried to move on from the kind of, email-based world and saving everything on your desktop-based world, a lot of it revolves around the push to move off of that revolves around security. >> Jeff: Right. >> Efficiencies, better distribution, better control over who has access to what. So my role is really to introduce digital production management systems. Digital daily systems, digital purchase order systems. Digital scheduling systems. >> Jeff: Right. >> Kind of take us into more of like a wholistic, one-way world that covers both the production side as well as the studio side. >> And where would you say you are on that journey? >> Year one, is what I would say. >> Year one. Early in year one, early days. >> So our department is called, the Production Business Intelligence Department, but that's really, I would say we have more enthusiasm for business intelligence than we do have knowledge of business intelligence. >> Jeff: Right, right. >> So phase one is really getting our systems rolled out. To get these digital systems in use, with 100% adoption, on all of our shows, and all of our studio and network users. Once we have that piece done, we can actually start to collect the data and make some use out of it. >> Right, right And how has kind of the efficiency in the workflow, I know you're still early days, how do you anticipate it really being impacted by moving to more cloud-based systems versus local, on your hard drive controlled? >> Yeah, so security is a hundred times better than it was before, right? Just because everything is hidden behind a password now. Access is much more controlled. Efficiency has increased many times over, as well. I'll say that we project, over the course of our first year with these systems, we will have reduced our email count, just within the studio, by 650,000. >> Well, who doesn't love that. >> Right, exactly. I keep telling them it's good. >> Jeff: Golly. >> Everything is more searchable now. >> Jeff: Right. >> Higher quality. We're getting things faster. Our PAs are no longer burning thousands of DVDs and distributing them all across town, so it's improved our world in many ways. >> Right, and how do you kind of boil that ocean. Is it kind of by department, is it by show, is it one little slice kind of spread really, really wide? I mean, that's a big roll out. You guys are a huge studio. >> When the department, that used to be called the Production Technology Department, and when it started eight, nine years ago, the approach was really like, let's build everything in house, and try to piece it out one by one. What we have learned is, that doesn't really work. It's really difficult to get adoption and it was going to take a huge workforce in order to build what we needed. >> Jeff: Right. >> So we started to go with the Best in Breed approach, with these applications. And what came with them was 24/7 support and kind of white glove training and admin services. >> Jeff: Right. >> So because I have a really small centralized team, they can focus on just the training administration. And we have really this third-party service team that comes with each one of these production management systems that we use. >> Right. >> So we've been able boil the ocean because we have a lot of help. >> Right. And the other nice thing is just because of the nature of the studios, teams kind of form around shows, right? So now you can onboard a new team around your infrastructure piece. They do the show for one season, two seasons, however many season. >> Brian: Yeah. >> Then they go away. >> Yeah, what's been really good is even though it's a huge training endeavor, for sure, with our production teams, because we have something like, 8,000 people on our freelance production teams at any time. And they're a transient workforce. They go from studio to studio and show to show. >> Jeff: Right. >> But I think something like 60 to 70% of the people that we hire, we've hired before. >> Jeff: Okay. >> So the good news is once we've trained them once, there's a good likelihood that we won't need to train them again. >> Right. And, so there's kind of the application centric piece of it, and then there's kind of the infrastructure piece behind the application. I mean, good news is, you didn't have it eight years ago, but I mean the development's on the infrastructure side around storage and bandwidth and CPU. Huge change from where it was before. I mean, could you even have done what you were hoping to do eight years, kind of compared to where you are today? No, I don't think, the companies just didn't exist at that point. That's right. So the companies weren't there because the technology wasn't there. >> Jeff: Right. >> Now they've both kind of aligned, and aligned at a good time, right? When I think people are ready to hear that we need to modernize the studio. There's so much competition out there, that we need to make sure that we're doing things as good or better than everyone else. >> Right. And you said security a bunch of times. >> Brian: Yeah. >> So was the security, was it a security hole? Was it people forgetting their laptop at the coffee shop? >> Brian: Yeah. >> I mean what were some of your main security concerns that you've now been able to address? >> It's interesting. So we're ABC Studios, but we do a lot of co-productions with Marvel Studios. And Marvel Studios culture is very security centric. And because we worked so hand-in-hand with them, we've been very cognizant of the security abilities of these applications as we bring them in. So I will say, we didn't have any big outbreaks, right? We didn't have, we had shows like Lost, that people were really concerned about. >> Right. >> Scripts getting out, but more recently, we haven't had these huge high security titles, but now that Marvel is onboard, it's made us very security conscious. >> Okay. And it's more early leaks that people getting access to the assets-- >> Yeah, mostly we're worried about scripts. >> Right, right. Really, mostly scripts, as opposed to images, or-- >> Well, you're right. Scripts and rough cuts, I would say. >> Right, right, right. Okay, so that's kind of the bat, the stick. In terms of a carrot, what were some of the benefits that you hoped to achieve or you are really starting to achieve on the carrot side of the equation? >> Well, so we're still in phase one, as I said, in kind of rolling out these applications. >> Right, we'll let you talk about this in private. We will not hold you to whatever you say that's being, actually in production. >> The carrot, is so we're now called production business intelligence, but we don't have much intelligence, at this point, so, now that we're seeing some light at the end of the tunnel, in terms of rolling out these systems, the hope is, the carrot is, we're going to be able to find some really great business insights from the data we collect. The kinds of questions we want to be able to answer are things like, which of our directors that are hire are costing us the most in production staff overtime. When an editor's cut delivers, and it delivers 11 minutes long, how does that correlate with the length and complexity of the script? You start to learn these things, and the hope will be that what was going to be a nine-day production schedule, we really can do it in eight. >> Jeff: Right. >> We'll have the data, not just anecdotally, but like real data to back that up. >> Right. Now I wonder, and don't tell me if you can't, but within kind of the whole budget of a movie, production, post-production, distribution, promotion, what piece is post-production? I mean, I just think of the complexity of it. It can be just a sinkhole, if it's not managed well. >> Yeah, as a part of the production, well it depends on the show, right? >> Right, right, you know, kind of a general-- >> The variance is in visual effects, right, but I would say 10 to 20% of the budget is post-production. >> Jeff: Okay. >> And the systems piece of it is much, much less. >> Jeff: Right, right. >> One, maybe one percent. >> Right. So you could make a pretty significant impact >> Yeah. >> On the budget by being more efficient. >> For sure. >> And leveraging that intelligence. >> Well, below the line, which is what these systems really do impact, so not just post-production but production, as well as two-thirds of the budget. So absolutely, I mean that's many millions of dollars. >> Right, right. Okay, so as you look forward, have you got any insights that are kind of helping you drive to the next place, or are you just kind of working down a road map as you look at 2017, I know we're a third of the way through, which I find really hard to believe. What's kind of on your agenda, what's next, where are you going next? >> I'd say we're still working down the roadmap. We have, like I said, we have documents figured out, we have digital dailies figured out, we have production purchase orders figured out, now we're going to start looking at asset management. And we're going to start looking at scheduling. In hopes that ultimately we can really, I guess the real vision here is that we can have kind of a production ratio, right? We can start to rate our productions against each other based on all of this information that we have, but it requires some additional systems first. >> All right, Brian. Well, I wish you, at least you've got 650,000 less emails. >> I know it's a good start. >> I mean that should free up a ton of time. >> Brian: Yes. >> That's a great start. All right, he's Brian Raleigh from ABC, I'm Jeff Frick. Again, thanks for stopping by. >> Brian: Thank you. >> All right, you're watching theCUBE, from NAB 2017. Thanks for watching. (techno music)

>> Narrator: Covering DataWorks Summit, Europe 2017, brought to you by Hortonworks. >> Welcome back to Munich everybody. This is The Cube. We're here live at DataWorks Summit, and we are the live leader in tech coverage. Steve Roberts is here as the offering manager for big data on power systems for IBM. Steve, good to see you again. >> Yeah, good to see you Dave. >> So we're here in Munich, a lot of action, good European flavor. It's my second European, formerly Hadoop Summit, now DataWorks. What's your take on the show? >> I like it. I like the size of the venue. It's the ability to interact and talk to a lot of the different sponsors and clients and partners, so the ability to network with a lot of people from a lot of different parts of the world in a short period of time, so it's been great so far and I'm looking forward to building upon this and towards the next DataWorks Summit in San Jose. >> Terri Virnig VP in your organization was up this morning, had a keynote presentation, so IBM got a lot of love in front of a fairly decent sized audience, talking a lot about the sort of ecosystem and that's evolving, the openness. Talk a little bit about open generally at IBM, but specifically what it means to your organization in the context of big data. >> Well, I am from the power systems team. So we have an initiative that we have launched a couple years ago called Open Power. And Open Power is a foundation of participants innovating from the power processor through all aspects, through accelerators, IO, GPUs, advanced analytics packages, system integration, but all to the point of being able to drive open power capability into the market and have power servers delivered not just through IBM, but through a whole ecosystem of partners. This compliments quite well with the Apache, Hadoop, and Spark philosophy of openness as it relates to software stack. So our story's really about being able to marry the benefits of open ecosystem for open power as it relates to the system infrastructure technology, which drives the same time to innovation, community value, and choice for customers as it relates to a multi-vendor ecosystem and coupled with the same premise as it relates to Hadoop and Spark. And of course, IBM is making significant contributions to Spark as part of the Apache Spark community and we're a key active member, as is Hortonworks with the ODPi organization forwarding the standards around Hadoop. So this is a one, two combo of open Hadoop, open Spark, either from Hortonworks or from IBM sitting on the open power platform built for big data. No other story really exists like that in the market today, open on open. >> So Terri mentioned cognitive systems. Bob Picciano has recently taken over and obviously has some cognitive chops, and some systems chops. Is this a rebranding of power? Is it sort of a layer on top? How should we interpret this? >> No, think of it more as a layer on top. So power will now be one of the assets, one of the sort of member family of the cognitive systems portion on IBM. System z can also be used as another great engine for cognitive in certain clients, certain use cases where they want to run cognitive close to the data and they have a lot of data sitting on System z. So power systems as a server really built for big data and machine learning, in particular our S822LC for high performance computing. This is a server which is landing very well in the deep learning, machine learning space. It offers the Tesla P100 GPU and with the NVIDIA NVLink technology can offer up to 2.8x bandwidth benefits CPU to GPU over what would be available through a PCIe Intel combination today. So this drives immediate value when you need to ensure that not just you're exploiting GPUs, but you of course need to move your data quickly from the processor to the GPU. >> So I was going to ask you actually, sort of what make power so well suited for big data and cognitive applications, particularly relative to Intel alternatives. You touched on that. IBM talks a lot about Moore's Law starting to hit its peak, that innovation is going to come from other places. I love that narrative 'cause it's really combinatorial innovation that's going to lead us in the next 50 years, but can we stay on that thread for a bit? What makes power so substantially unique, uniquely suited and qualified to run cognitive systems and big data? >> Yeah, it actually starts with even more of the fundamentals of the power processors. The power processor has eight threads per core in contrast to Intel's two threads per core. So this just means for being able to parallelize your workloads and workloads that come up in the cognitive space, whether you're running complex queries and need to drive SQL over a lot of parallel pipes or you're writing iterative computation, the same data set as when you're doing model training, these can all benefit from highly parallelized workloads, which can benefit from this 4x thread advantage. But of course to do this, you also need large, fast memory, and we have six times more cache per core versus Broadwell, so this just means you have a lot of memory close to the processor, driving that throughput that you require. And then on top of that, now we get to the ability to add accelerators, and unique accelerators such as I mentioned the NVIDIA in the links scenario for GPU or using the open CAPI as an approach to attach FPGA or Flash to get access speeds, processor memory access speeds, but with an attached acceleration device. And so this is economies of scale in terms of being able to offload specialized compute processing to the right accelerator at the right time, so you can drive way more throughput. The upper bounds are driving workload through individual nodes and being able to balance your IO and compute on an individual node is far superior with the power system server. >> Okay, so multi-threaded, giant memories, and this open CAPI gives you primitive level access I guess to a memory extension, instead of having to-- >> Yeah, pluggable accelerators through this high speed memory extension. >> Instead of going through, what I often call the horrible storage stack, aka SCSI, And so that's cool, some good technology discussion there. What's the business impact of all that? What are you seeing with clients? >> Well, the business impact is not everyone is going to start with supped up accelerated workloads, but they're going to get there. So part of the vision that clients need to understand is to begin to get more insights from their data is, it's hard to predict where your workloads are going to go. So you want to start with a server that provides you some of that upper room for growth. You don't want to keep scaling out horizontally by requiring to add nodes every time you need to add storage or add more compute capacity. So firstly, it's the flexibility, being able to bring versatile workloads onto a node or a small number of nodes and be able to exploit some of these memory advantages, acceleration advantages without necessarily having to build large scale out clusters. Ultimately, it's about improving time to insights. So with accelerators and with large memory, running workloads on a similar configured clusters, you're simply going to get your results faster. For example, recent benchmark we did with a representative set of TPC-DS queries on Hortonworks running on Linux and power servers, we're able to drive 70% more queries per hour over a comparable Intel configuration. So this is just getting more work done on what is now similarly priced infrastructure. 'Cause power family is a broad family that now includes 1U, 2U, scale out servers, along with our 192 core horsepowers for enterprise grade. So we can directly price compete on a scale out box, but we offer a lot more flexible choice as clients want to move up in the workload stack or to bring accelerators to the table as they start to experiment with machine learning. >> So if I understand that right, I can turn two knobs. I can do the same amount of work for less money, TCO play. Or, for the same amount of money, I can do more work. >> Absolutely >> Is that fair? >> Absolutely, now in some cases, especially in the Hadoop space, the size of your cluster is somewhat gated by how much storage you require. And if you're using the classic scale up storage model, you're going to have so many nodes no matter what 'cause you can only put so much storage on the node. So in that case, >> You're scaling storage. >> Your clusters can look the same, but you can put a lot more workload on that cluster or you can bring in IBM, a solution like IBM Spectrum Scale our elastic storage server, which allows you to essentially pull that storage off the nodes, put it in a storage appliance, and at that point, you now have high speed access to storage 'cause of course the network bandwidth has increased to the point that the performance benefit of local storage is no longer really a driving factor to a classic Hadoop deployment. You can get that high speed access in a storage appliance mode with the resiliency at far less cost 'cause you don't need 3x replication, you just have about a 30% overhead for the software erasure coding. And now with your compete nodes, you can really choose and scale those nodes just for your workload purposes. So you're not bound by the number of nodes equal total storage required by storage per node, which is a classic, how big is my cluster calculation. That just doesn't work if you get over 10 nodes, 'cause now you're just starting to get to the point where you're wasting something right? You're either wasting storage capacity or typically you're wasting compute capacity 'cause you're over provisioned on one side or the other. >> So you're able to scale compute and storage independent and tune that for the workload and grow that resource efficiently, more efficiently? >> You can right size the compute and storage for your cluster, but also importantly is you gain the flexibility with that storage tier, that data plan can be used for other non-HDFS workloads. You can still have classic POSIX applications or you may have new object based applications and you can with a single copy of the data, one virtual file system, which could also be geographically distributed, serving both Hadoop and non-Hadoop workloads, so you're saving then additional replicas of the data from being required by being able to onboard that onto a common data layer. >> So that's a return on asset play. You got an asset that's more fungible across the application portfolio. You can get more value out of it. You don't have to dedicate it to this one workload and then over provision for another one when you got extra capacity sitting here. >> It's a TCO play, but it's also a time saver. It's going to get you time to insight faster 'cause you don't have to keep moving that data around. The time you spend copying data is time you should be spending getting insights from the data, so having a common data layer removes that delay. >> Okay, 'cause it's HDFS ready I don't have to essentially move data from my existing systems into this new stovepipe. >> Yeah, we just present it through the HDFS API as it lands in the file system from the original application. >> So now, all this talk about rings of flexibility, agility, etc, what about cloud? How does cloud fit into this strategy? What do are you guys doing with your colleagues and cohorts at Bluemix, aka SoftLayer. You don't use that term anymore, but we do. When we get our bill it says SoftLayer still, but any rate, you know what I'm talking about. The cloud with IBM, how does it relate to what you guys are doing in power systems? >> Well the cloud is still, really the born on the cloud philosophy of IBM software analytics team is still very much the motto. So as you see in the data science experience, which was launched last year, born in the cloud, all our analytics packages whether it be our BigInsights software or our business intelligence software like Cognos, our future generations are landing first in the cloud. And of course we have our whole arsenal of Watson based analytics and APIs available through the cloud. So what we're now seeing as well as we're taking those born in the cloud, but now also offering a lot of those in an on-premise model. So they can also participate in the hybrid model, so data science experience now coming on premise, we're showing it at the booth here today. Bluemix has a on premise version as well, and the same software library, BigInsights, Cognos, SPSS are all available for on prem deployment. So power is still ideal place for hosting your on prem data and to run your analytics close to the data, and now we can federate that through hybrid access to these elements running in the cloud. So the focus is really being able to, the cloud applications being able to leverage the power and System z's based data through high speed connectors and being able to build hybrid configurations where you're running your analytics where they most make sense based upon your performance requirements, data security and compliance requirements. And a lot of companies, of course, are still not comfortable putting all their jewels in the cloud, so typically there's going to be a mix and match. We are expanding the footprint for cloud based offerings both in terms of power servers offered through SoftLayer, but also through other cloud providers, Nimbix is a partner we're working with right now who actually is offering our Power AI package. Power AI is a package of open source, deep learning frameworks, packaged by IBM, optimized for Power in an easily deployed package with IBM support available. And that's, could be deployed on premise in a power server, but also available on a pay per drink purpose through the Nimbix cloud. >> All right, we covered a lot of ground here. We talked strategy, we talked strategic fit, which I guess is sort of a adjunct to strategy, we talked a little bit about the competition and where you differentiate, some of the deployment models, like cloud, other bits and pieces of your portfolio. Can we talk specifically about the announcements that you have here at this event, just maybe summarize for use? >> Yeah, no absolutely. As it relates to IBM, and Hadoop, and Spark, we really have the full stack support, the rich analytics capabilities that I was mentioning, deep insight, prescriptive insights, streaming analytics with IBM Streams, Cognos Business Intelligence, so this set of technologies is available for both IBMs, Hadoop stack, and Hortonworks Hadoop stack today. Our BigInsights and IOP offering, is now out for tech preview, their next release their 4.3 release, is available for technical preview will be available for both Linux on Intel, Linux on power towards the end of this month, so that's kind of one piece of new Hadoop news at the analytics layer. As it relates to power systems, as Hortonworks announced this morning, HDP 2.6 is now available for Linux on power, so we've been partnering closely with Hortonworks to ensure that we have an optimized story for HDP running on power system servers as the data point I shared earlier with the 70% improved queries per hour. At the storage layer, we have a work in progress to certify Hortonworks, to certify Spectrum Scale file system, which really now unlocks abilities to offer this converged storage alternative to the classic Hadoop model. Spectrum Scale actually supports and provides advantages in both a classic Hadoop model with local storage or it can provide the flexibility of offering the same sort of multi-application support, but in a scale out model for storage that it also has the ability to form a part of a storage appliance that we call Elastic Storage Server, which is a combination of power servers and high density storage enclosures, SSD or spinning disk, depending upon the, or flash, depending on the configuration, and that certification will now have that as an available storage appliance, which could underpin either IBM Open Platform or HDP as a Hadoop data leg. But as I mentioned, not just for Hadoop, really for building a common data plane behind mixed analytics workloads that reduces your TCO through converged storage footprint, but more importantly, provides you that flexibility of not having to create data copies to support multiple applications. >> Excellent, IBM opening up its portfolio to the open source ecosystem. You guys have always had, well not always, but in the last 20 years, major, major investments in open source. They continue on, we're seeing it here. Steve, people are filing in. The evening festivities are about to begin. >> Steve: Yeah, yeah, the party will begin shortly. >> Really appreciate you coming on The Cube, thanks very much. >> Thanks a lot Dave. >> You're welcome. >> Great to talk to you. >> All right, keep it right there everybody. John and I will be back with a wrap up right after this short break, right back.