(upbeat music) >> Hey everyone. Welcome to theCUBE's special program series "Women of the Cloud", brought to you by AWS. I'm your host for the program, Lisa Martin. Very pleased to welcome back one of our alumni to this special series, Dr. Tendu Yogurtcu joins us, the CTO of Precisely. >> Lisa: Tendu, it's great to see you, it's been a while, but I'm glad that you're doing so well. >> Geez, it's so great seeing you too, and thank you for having me. >> My pleasure. I want the audience to understand a little bit about you. Talk to me a little bit about you, about your role and what are some of the great things that you're doing at Precisely. >> Of course. As CTO, my current role is driving technology vision and innovation, and also coming up with expansion strategies for Precisely's future growth. Precisely is the leader in data integrity. We deliver data with trust, with maximum accuracy, consistency, and also with context. And as a CTO, keeping an eye on what's coming in the business space, what's coming up with the emerging challenges is really key for me. Prior to becoming CTO, I was General Manager for the Syncsort big data business. And previously I had several engineering and R&D leadership roles. I also have a bit of academia experience. I served as a part-time faculty in computer science department in a university. And I am a person who is very tuned to giving back to my community. So I'm currently serving as a advisory board member in the same university. And I'm also serving as a advisory board member for a venture capital firm. And I take pride in being a dedicated advocate for STEM education and STEM education for women in particular, and girls in the underserved areas. >> You have such a great background. The breadth of your background, the experience that you have in the industry as well in academia is so impressive. I've known you a long time. I'd love the audience to get some recommendations from you. For those of the audience looking to grow and expand their careers in technology, what are some of the things that you that you've experienced that you would recommend people do? >> First, stay current. What is emerging today is going to be current very quickly. Especially now we are seeing more change and change at the increased speed than ever. So keeping an eye on on what's happening in the market if you want to be marketable. Now, some of the things that I will say, we have shortage of skills with data science, data engineering with security cyber security with cloud, right? We are here talking about cloud in particular. So there is a shortage of skills in the emerging technologies, AI, ML, there's a shortage of skills also in the retiring technologies. So we are in this like spectrum of skills shortage. So stay tuned to what's coming up. That's one. And on the second piece is that the quicker you tie what you are doing to the goals of the business, whether that's revenue growth whether that's customer retention or cost optimization you are more likely to grow in your career. You have to be able to articulate what you are doing and how that brings value to business to your boss, to your customers. So that becomes an important one. And then third one is giving back. Do something for the women in technology while being a woman in technology. Give back to your community whether that's community is gender based or whether it's your alumni, whether it's your community social community in your neighborhood or in your country or ethnicity. Give back to your community. I think that's becoming really important. >> I think so too. I think that paying it forward is so critical. I'm sure that you have a a long list of mentors and sponsors that have guided you along the way. Giving back to the community paying it forward I think is so important. For others who might be a few years behind us or even maybe have been in tech for the same amount of time that are looking to grow and expand their career having those mentors and sponsors of women who've been through the trenches is inspiring. It's so helpful. And it really is something that we need to do from a diversity perspective alone, right? >> Correct. Correct. And we have seen that, we have seen, for example Covid impact in women in particular. Diverse studies done by girls who quote on Accenture that showed that actually 50% of the women above age 35 were actually dropping out of the technology. And those numbers are scary. However, on the other side we have also seen incredible amount of technology innovation during that time with cloud adoption increasing with the ability to actually work remotely if you are even living in not so secure areas, for example that created more opportunities for women to come back to workforce as well. So we can turn the challenges to opportunities and watch out for those. I would say tipping points. >> I love that you bring up such a great point. There are so, so the, the data doesn't lie, right? The data shows that there's a significant amount of churn for women in technology. But to your point, there are so many opportunities. You mentioned a minute ago the skills gap. One of the things we talk about often on theCUBE and we're talking about cybersecurity which is obviously it's a global risk for companies in every industry, is that there's massive opportunity for people of, of any type to be able to grow their skills. So knowing that there's trend, but there's also so much opportunity for women in technology to climb the ladder is kind of exciting. I think. >> It is. It is exciting. >> Talk to me a little bit about, I would love for the audience to understand some of your hands-on examples where you've really been successful helping organizations navigate digital transformation and their entry and success with cloud computing. What are some of those success stories that you're really proud of? >> Let me think about, first of all what we are seeing is with the digital transformation in general, every single business every single vertical is becoming a technology company. Telecom companies are becoming a technology company. Financial services are becoming a technology company and manufacturing is becoming a technology company. So every business is becoming technology driven. And data is the key. Data is the enabler for every single business. So when we think about the challenges, one of the examples that I give a big challenge for our customers is I can't find the critical data, I can't access it. What are my critical data elements? Because I have so high volumes growing exponentially. What are the critical data elements that I should care and how do I access that? And we work at Precisely with 99 of Fortune 100. So we have two 12,000 customers in over a hundred countries which means we have customers whose businesses are purely built on cloud, clean slate. We also have businesses who have very complex set of data platforms. They have financial services, insurance, for example. They have critical transactional workloads still running on mainframes, IBM i servers, SAP systems. So one of the challenges that we have, and I work with key customers, is on how do we make data accessible for advanced analytics in the cloud? Cloud opens up a ton of open source tools, AI, ML stack lots of tools that actually the companies can leverage for that analytics in addition to elasticity in addition to easy to set up infrastructure. So how do we make sure the data can be actually available from these transactional systems, from mainframes at the speed that the business requires. So it's not just accessing data at the speed the business requires. One of our insurance customers they actually created this data marketplace on Amazon Cloud. And the, their challenge was to make sure they can bring the fresh data on a nightly basis initially and which became actually half an hour, every half an hour. So the speed of the business requirements have changed over time. We work with them very closely and also with the Amazon teams on enabling bringing data and workloads from the mainframes and executing in the cloud. So that's one example. Another big challenge that we see is, can I trust my data? And data integrity is more critical than ever. The quality of data, actually, according to HBR Harvard Business Review survey, 47% of every new record of data has at least one critical data error, 47%. So imagine, I was talking with the manufacturing organization couple of weeks ago and they were giving me an example. They have these three letter quotes for parts and different chemicals they use in the manufacturing. And the single letter error calls a shutdown of the whole manufacturing line. >> Wow. >> So that kind of challenge, how do I ensure that I can actually have completeness of data cleanness of data and consistency in that data? Moreover, govern that on a continuous basis becomes one of the use cases that we help customers. And in that particular case actually we help them put a data governance framework and data quality in their manufacturing line. It's becoming also a critical for, for example ESG, environment, social and governance, supply chain, monitoring the supply chain, and assessing ESG metrics. We see that again. And then the third one, last one. I will give an example because I think it's important. Hybrid cloud becoming critical. Because there's a purest view for new companies. However, facilitating flexible deployment models and facilitating cloud and hybrid cloud is also where we really we can help our customers. >> You brought up some amazingly critical points where it comes to data. You talked about, you know, a minute ago, every company in every industry has to become a technology company. You could also say every company across every industry has to become a data company. They have to become a software company. But to your point, and what it sounds like precisely is really helping organizations to do is access the data access data that has high integrity data that is free of errors. Obviously that's business critical. You talked about the high percentage of errors that caused manufacturing shutdown. Businesses can't, can't have that. That could potentially be life-ending for an organization. So it sounds like what you're talking about data accessibility, data integrity data governance and having that all in real time is table stakes for businesses. Whether it's your grocery store, your local coffee shop a manufacturing company, and e-commerce company. It's table stakes globally these days. >> It is, and you made a very good point actually, Lisa when you talked about the local coffee shop or the retail. One other interesting statistic is that almost 80% of every data has a location attribute. So when we talk about data integrity we no longer talk about just, and consistency of data. We also talk about context, right? When you are going, for example, to a new town you are probably getting some reminders about where your favorite coffee shop is or what telecom company has an office in that particular town. Or if you're an insurance company and a hurricane is hitting southern Florida. Then you want to know how the path of that hurricane is going to impact your customers and predict the claims before they happen. Also understand the propensity of the potential customers that you don't yet have. So location and context, those additional attributes of demographics, visitations are creating actually more confident business insights. >> Absolutely. And and as the consumer we're becoming more and more demanding. We want to be able to transact things so easily whether it's in our personal life at the grocery store, at that cafe, or in our business life. So those demands from the customer are also really influencing the direction that companies need to go. And it's actually, I think it's quite exciting that the amount of personalization the location data that you talk about that comes in there and really helps companies in every industry deliver these the cloud can, these amazing, unique personalized experiences that really drive business forward. We could talk about that all day long. I have no problem. But I want to get in our final minutes here, Tendu. What do you see as in your crystal ball as next for the cloud? How do you see your role as CTO evolving? >> Sure. For what we are seeing in the cloud I think we will start seeing more and more focus on sustainability. Sustainable technologies and governance. Obviously cloud migrations cloud modernizations are helping with that. And we, we are seeing many of our customers they started actually assessing the ESG supply chain and reporting on metrics whether it's the percentage of face or energy consumption. Also on the social metrics on diversity age distribution and as well as compliance piece. So sustainability governance I think that will become one area. Second, security, we talked about IT security and data privacy. I think we will see more and more investments around those. Cybersecurity in particular. And ethical data access and ethics is becoming center to everything we are doing as we have those personalized experiences and have more opportunities in the cloud. And the third one is continued automation with AI, ML and more focus on automation because cloud enables that at scale. And the work that we need to do is too time-intensive and too manual with the amount of data. Data is powering every business. So automation is going to be an increased focus how my role evolves with that. So I have this unique combination. I have been open to non-linear career paths throughout my growth. So I have an understanding of how to innovate and build products that solve real business problems. I also have an understanding of how to sell them build partnerships that combined with the the scale of growth, the hyper growth that we have absorbed in precisely 10 times growth within the last 10 years through a combination of organic innovation and acquisitions really requires the speed of change. So change, implementing change at scale as well as at speed. So taking those and bringing them to the next challenge is the evolution of my role. How do I bring those and tackle keep an eye on what's coming as a challenge in the industry and how they apply those skills that I have developed throughout my career to that next challenge and evolve with it, bring the innovation to data to cloud and the next challenge that we are going to see. >> There's so much on the horizon. It's, there are certainly challenges, you know within technology, but there's so much opportunity. You've done such a great job highlighting your career path the, the big impact that you're helping organizations make leveraging cloud and the opportunity that's there for the rest of us to really get in there get our hands dirty and solve problems. Tendu, I always love our conversations. It's been such a pleasure having you back, back on theCUBE. Thank you for joining us on this special program series today. >> Thank you Lisa. And also thanks to AWS for the opportunity. >> Absolutely. This is brought, brought to us by AWS. For Dr.Tendu, you are good to go. I'm Lisa Martin. You're watching theCUBE special program series Women of the Cloud. We thank you so much for watching and we'll see you soon. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel, AWS and our community partners. Hey, is Keith Townsend, principal at CTO Adviser, and you're watching the Cube virtual coverage of AWS reinvent 2020. I'm really excited whenever we get toe talk to actual end users. Builders. The conversation is dynamic. This is no exception. Back on the show, Al Vanish despondent head off architectures at logic I've been ish. Welcome back to the show. >>Thanks, Kate. Good to be here >>and on the other side of my screen or how you depend on how you're looking at it is Anthony Brooks Williams C E O off HBR Anthony, Welcome back to the Cube. I know your kind of tired of seeing us, but the conversation is gonna be good, I promise. >>Thanks very much. Look forward to being here and great as you said to talk about a use case for the customer in the real world. >>So I'll be let's start off by talking about lodge attacking. What are you guys doing in a W s in general? I mean, e no. Every company has public cloud, but Logitech and AWS and Public Cloud doesn't naturally come to mind. Help educate the audience. What do you guys doing? >>Sure, so traditionally, audience knows Logitech as the Mice and keyboard company, but we do have a lot of brands which are cool brands off logic tech If you know about gaming, Logitech G is a huge brand for us. We are in video collaboration space. We compete with the likes off Ciscos of the world, where we have hardware that goes on bond works with Zoom Google as well as Microsoft ecosystems. That has been a huge success in a B two b well for us. Beyond music industry gaming as an Astro gaming Jay Bird head phones for athletes. We are also in security system space. On top of that were also in the collaboration space off streaming as in stream labs so a Z can see logic has grown toe where that a lot off use cases, apart from just peripherals, is out there. We connected devices, so we're also looking to move towards a cloud ecosystem where we could be in on on our toes, toe provisioning information on DNA, make sure we are computing to the best of the world. So we are in AWS. We do a lot more in AWS now, compared to what we used to do in the past last five years has seen a change and a shift towards more cloud public cloud usage pure SAS environments in the ws as well And we provisioned data for analysis and essentially a data driven enterprise. Now more so on V as we move towards more future >>and Anthony talked to me about not necessarily just largest heck, but the larger market. How are you seeing companies such as logic? Heck take advantage off A W s and Public cloud. >>Yeah, but I think you mean ultimately we've seen it accelerated the show. Me Castle's just looking for a better way to connect with their prospects, you know, and leverage data in doing so. And we've seen this this driver around digital transformation and that's just being sped up the shirt, given what we've seen around covert and so a lot more companies have really pushed forward and adopting, you know, the infrastructure and the availability off systems and solutions that you find in a platform such as AWS on bets that we've seen grand deduction from our side of customers doing that, we provide the most efficient way of protesters to move data to so platforms such as I don't yes, and that's what we've seen. A big uptick picture. >>So let's focus the conversation around data data, the new oil. We've heard the taglines. Let's put some meat on the bone, so to speak and talk through How are you at logic Tech using real time data in the public cloud? >>Sure, Yeah. I mean, traditionally, if you look at it, uh, logic could selling hardware. Andi hope it >>works for >>the end consumer. Uh, we would not necessarily have an insight into how that product is being used. I think come fast forward. Today's world. It's a connected devices environment. You want to make sure when you sell something, it is working for that consumer. You would want them to be happy about that product, ensuring a seamless experience. Eso customer experience is big. You might want to see a repeat customer come about right. So So the intent is to have a lot off. It is connected experience where you could provisional feedback loop to the engineering team toe to ensure stability off the product, but also enhancements around that product in terms off usage patterns. And and we play a big role with hardware in what you're gaming, for example. And as you can see, that whole industry is growing toe where everything is connected. Probably people do not buy anything, which is a static discussing thing. It's all online gaming. So we want to ensure we don't add Leighton. See in the hardware that we have, ensuring a successful experience and repeat customers right? The essential intent is at the end of the day, to have success with what you sell because there's obviously other options on the market and you want to make sure our customers are happy with the hardware they are investing. Maurin that hardware platform and adding different, very fills along with it so that seamless experiences where we wanna make sure it's connected devices to get that insight. We also look at what people are saying about our products in terms off reviews on APS are on retail portals to ensure we we hear the wise off customer on channel. How's that energy in a positive way to improve the products as well as trying to figure out if there are marketing opportunities were you could go across sailing up cells, so that's essentially driving business towards that success, and at the end of it, that would essentially come up with a revenue generation model >>for us. So Anthony talked to me about how HBR fits into this, because when I look at cloud big, that can be a bit overbearing, like, where's where's the starting point? >>So I mean, for us, you mean the starting point Answer questions around. Acquiring the data data is generated in many places across organizations in many different platforms and many systems. And so we have the ability to have a very efficient technique in the way we go acquire data the way we capture data through this technique called CBC Chinese share the capture where you're feeding incremental updates off off the data across the network. That's the most efficient way to move this data. Firstly, across a wide area network cloud is an endpoint. Uh, you mean off that, And so, firstly, we specializing in supporting many different source systems and so we can acquire that data very efficiently, put it into our into a very scalable, flexible architecture that we have. That's that's a great foot for this modern world of great foot for the cloud. So not only can we capture data from many different source systems, their complexities and a lot of these type of the moments that customers have, we could take the data and move it very efficiently across that network at scale. Because we know, as you've said, data is the new oil that's the lifeblood of organizations today. So we can move that data efficiently at scale across the network and then put it into a system such a snowflake running in AWS like we do for a hobby and a larger taken. So that's really where we fit. I mean, we can, you know, we support data taken from many sources, too many different target systems. We make sure that data is highly accurate. When we move that data across that matches what was in the source of matches, what's in the in the target system. And we do that in this particular use case and what we see predominantly today, the source systems are capturing the data typically today. Still generated on Prem could be data that's sitting in an SFP environment. Unpack that data. Decode that data is to be complex to get out and understand it on moving across and put it in their target system, that predominance sitting in the cloud for all the benefits that we see that the cloud brings around elasticity and efficiency and operational costs the most type of things. And that's probably human in where we fit into this picture. >>You know, I think if I add a little bit there, right, So to Anthony's point for us, we generate a lot of data. You're looking at billions off rolls a day from the edge where people like you and I are using logic devices and we also have a lot off prp transactions That going so the three V s Typically that they call about big data is like the variety off data volume of data at velocity that you want to consume it. So the intent is if you need to be data driven, the data should be available for business consumption as it is being generated very near real time, and that the intent for some of these platforms like H we are, is How efficiently could you move that data, whether it's on Prem or a different cloud into AWS on giving it for business consumption of business analysis in near real time. So you know we strive, Toby Riel time. Whether it's data from China in our factory, on the shop floor, whether it's being generated from people like you and I playing a game for eight hours on generating so many events, we're gonna ensure all that data is being available for business analysis and gone out of those days where we would load that data once a day. And in the hope that we do a weekly analysis right today, we do analysis on make business decisions on that data as the data is being generated. And that's the key to success with such platforms, where we want to make sure we also look at build vs buy rather than us doing all that core and trying toe in just that data we obviously partner with which we are in certain application platforms to ensure stability off it. And they have proven with their experience the I P or the knowledge around how to build those platforms, which even if we go build it, we might need bigger teams to build that. I would rather rely on partners for that capability. And I bring more business value by enabling and implementing such solutions. >>So let's put a little color around that skill whenever I talk to CDOs. Chief data officers, data architects One of the biggest problems that they have in these massive systems you're talking about getting data from E. AARP uh, Internet of things devices, etcetera is simple data transformation. E t l data scientists spend a good droid at a time, maybe sometimes 80% of their time on that data transformation process that slows down the ability to get answers to critical business. Analytic questions. How is HBR assistant you guys and curling down at time for detail? >>Absolutely. So we we do not. We went to cloud about five years back, and the methodology that you talk about e t. L is sort of a point back in the day when you would do, you know, maybe a couple of times a day ingestion. So it's like in the the transition off the pipeline. As you are ingesting data, you would transform and massage the return, enhance the data and provisioned it for business consumption. Today we do lt we extract loaded into target and natively transform it as needed from business consumption. So So we look at each. We are, for example, is, uh, we're replicating all off our e r P data into snowflake in the cloud for real time ingestion and consumption. Uh, if you do all of this analysis on article side to it, typically you would have ah, processing where you would put put in a job toe, get that data out, and analysis comes back to you in a couple of hours out here, you could be slicing and dicing the data as needed on it's all self serve on provisioning. We do not build analysis foreign users. Neither do we do a lot off the data science. But we want to make sure when businesses using that data they can act on that as it's available on the example is we had a processing back in the day with demand forecasting, which we do for every product off logic for 52 weeks, looking ahead for for every week, right, and it will run for a couple of days that processing today with such platforms on in public Lot. We do that in an hour's time. Right now That's critical for business success because you want to know the methodologies you feel need Tofail or have challenges. You probably wanna have them now rather than wait a couple of days for that process in the show up, and then you do not have enough time to, at just the parameters are bringing back some other business process toe augmented. So that's what we look at. The return on investment for such investment are essentially ensuring business continuity and success outfront on faster time to deliver. >>Yeah, >>so, Anthony, this seems like this would really change the conversation within enterprises. The target customer or audience really changes from kind of this IittIe centric movement tome or strategic move. We talked to me about the conversations you've had, what customers and how this has transformed their business. >>Yeah, a few things to unpack there, um, one. You mean, obviously, customs wanna make decisions on the freshest data, so they typically relied on in the past on these batch orientated tough data movement techniques, which which will be touched on there and how we're able to reduce that that time window. Let them make decisions on the freshest data where that takes, you, choose into other parts of organizations. Because, Azzawi said, already, I mean, we know that is the lifeblood of them. There was many, I would say, Typically, I t semi, but let's call it data. Seven people sitting in the both side of organizations, if not Mawr, than used to sit in the legacy I t side. They want access to this data. They want to be able to access their daily easy. And so one of these things cloud based system SAS based systems have made that a lot easier for them. And the conversations. We have a very much driven from not only the chief data officers, but the CEOs. Now they know in order to get the advantage to win. To survive in today's times, they need to be data driven organizations, and it sounds cliche. We hear these digital transformation stories and data driven taglines. They get thrown out there, but what we've seen is where it's really it's been put to toss this year it is happening. Projects that would happen 9 12 months have been given to month Windows to happen because it's a matter of survival and so that's what's really driven. And then you also have the companies that benefit as well. You mean we're fortunate that we are able as a company globally, with composer of all to work from her very efficiently. But then support customers like Obvious who or providing these work from home technology systems that can enable another? The semester It's really moved. That's driven down from being purely I t driven to its CEO, CEO, CEO driven because its's what they've got to do. It z no longer just table stakes. >>I >>think the lines are great, right way we roll up into CEO and like I work for the CEO at at large detect. But we strive to be more service oriented than support. So I t was traditionally looked at as a support our right. But we obviously are enabling the enterprise to be data driven, so we strive to be better at what we do and how we position ourselves. As as more off service are connected to business problem, we understand the business problem and the challenge that they have on and ensuring we could find solutions and solution architectures around that problem to ensure success for that, right? And that's the key to it. Whether we build, vs, buy it. It's all about ensuring business doesn't have toe find stopgap solutions to be successful in finding a solution for their problem. >>Avi Anthony, I really appreciate you guys taking the time to peel back the layers and help the audience understand how to take thes really abstract terms and make them rial for getting answers on real time data and kind of blowing away these concepts of E t l and data transformations and how toe really put data toe work using public cloud resource sources against their real time data assets. Thank you for joining us on this installment of the Cube virtual as we cover A W s re event, make sure to check out the portal and Seymour great coverage off this exciting area off data and data analysis

>>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 Volante. 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 cohosts from ThoughtSpot first chief data strategy officer, the ThoughtSpot is Cindy Hausen. Cindy 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. Cindy 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. Cindy. 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, sedition air. Hello. Sudheesh how are you doing today? I am validating. It's good to talk to you again. That's great to see you. Thanks so much for being here now Sateesh 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. >>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. Um, look, since we have all been, you know, cooped up in our homes, I know that the vendors like us, we have amped up know 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, has we planned through this? You know, we are living through these difficult times. You want an event to be this event, to be more of an uplifting and inspiring event. Now, the challenge is how do you do that with the team being change agents? Because teens can, as much as we romanticize it, it is not one of those uplifting things that everyone wants to do, or like through the VA. 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, uh, 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, 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've may feel that I'm, 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 necessarily the group of people that we are brought in. The four people, including Cindy, 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. >>So we're going to take a hard pivot now and go from football to Ternopil 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, Cindy, 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 parameterized reports on premises, data, warehouses, or not even that operational reports at best one enterprise, nice 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. None of this. Oh, well, I didn't invent that. I'm not going to look at that. There's still proud of that ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas, 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 double monetized, not just for people, how are users or analysts, but really at the of impact what we like to call the new decision makers or really the front line 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 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 of 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 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 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 thoughts about 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, or Azure synapse or Google big query, they do not. >>They re 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 read any of my books or used any of the maturity models out there, whether the Gardner it score that I worked on, or the data warehousing Institute also has the 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, basing 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 us federal government said, well, you can't turn them off. >>He 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 with them 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 with them, 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 seventies or eighties 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 with them. 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 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 and 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 Masa, Pharaoh, 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. >>Very happy to be here and, uh, looking forward to, uh, to talking to all of you today. So as we look to move organizations to a data-driven, uh, capability into the future, there is a lot that needs to be done on the data side, but also how did it connect and enable different business teams and technology teams into the future. As we look across, uh, 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, 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 being, you gone to Yahoo and you search for what you want search to find an answer ThoughtSpot for us, it's 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 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 Elequil 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 the portion of us though, is culture. So how do we engage with the business teams and bring the, the, the it teams together to really hit the drive, these holistic end to end solution, the 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, as upon products, solutions or partnerships into the future. These are really some of the keys that, uh, that become crucial as you move forward, right, uh, into this, uh, 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. And these, 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, those capabilities. And those solutions forward as we go through this journey, uh, boasted 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 has 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 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 and to support your business there's important, your employees, your operations teams, and so forth, and really creating that full integration in that ecosystem is really when he talked to get large dividends from his investments into the future. But that being said, uh, I hope you enjoyed the segment on how to become and how to drive a data driven organization. And I'm 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 this rusted. And how long have you been at Western union? >>Uh, well in nine months. So just, uh, just started this year, but, uh, there'd be some great opportunities and great changes and we were 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, Schneider electric, but even going back to Sam's clubs. Gustavo. Welcome. >>So hi everyone. My name is Gustavo Canton and thank you so much, Cindy, for the intro, as you mentioned, doing transformations is a high effort, high reward situation. I have empowerment transformations and I have less 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, 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 is great to be, you know, stay in tune and have the skillset and the Koresh. But for me personally, to be honest, to have this courage is not about Nadina afraid. You're always afraid when you're making big changes in 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, eh, 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 Cindy has mentioned, these topic about culture is sexually gaining, gaining more and more traction. And in 2018, there was a story from HBR and he wants 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 in set us state, eh, deadline to say, Hey, in two years, we're going to make this happen. Why 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 examples of some of the roadblocks that I went through. As I think the transformations most recently, as Cindy 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 having successful while 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, 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 the example that I have with ThoughtSpot, right? >>We went on implementation and a lot of the way the it team function. So the leaders look at technology, they look at it from the prison of the prior auth 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 this experience you have at home is 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, 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 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. And 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 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 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 your organization. >>Maturity is 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 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 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 a hundred 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 hundred dollars. >>But now let's say you have 80% perfect data and 20% flow data by using this assumption that Florida is 10 times as costly as perfect data. Your total costs now becomes $280 as opposed to a hundred dollars. This just for you to really think about as a CIO CTO, CSRO CEO, are we really paying attention and really close in the gaps that we have on our data infrastructure. If we don't do that, it's hard sometimes to see this 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 various, right. I think the key is I am in analytics. I know statistics obviously, and, and, 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 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 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 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 where 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 Tablo to other tools like, you know, you need to really explain them. >>What is the difference in how these two 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 Cindy'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 in shape the culture so people can understand why you truly need to invest, but I meant analytics. >>And so what I'm showing here is an example of how do we use basically 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, our safe user experience and adoption. So for our safe 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. 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 teams and the users in HR safety and other areas that might be, eh, basically stakeholders in this whole process. >>So just to summarize this kind of effort takes a lot of energy. You hire a change agent, you need to have the 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 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 says to say, thank you for everybody who has believed, obviously in our vision, everybody wants to believe in, you know, the word that we were trying to do and to make the life for, you know, workforce or customers that 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. We, the accomplishments of this transformation, and I just, 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, where we, 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 bodies, well worth it. And with that said, I hope you are well. And it's been a pleasure talking to you. Take care. Thank you, Gustavo. That was amazing. All right, let's go to the panel. >>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, 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. We'll COVID is broken everything. And it's great to hear from our experts, you know, how to move forward. So let's get right into, so Gustavo, let's start with you. If, if I'm an aspiring change agent and let's say I'm a, 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 try to do is I try to go into areas, different certain transformations that make me, you know, stretch and develop as a leader. That's what I'm looking to do. So I can help to inform the functions organizations and do the change management decision of mindset as required for these kinds of efforts. A thank you for that, that is inspiring. And, and Sydney, you love data. And the data's pretty clear that diversity is a good business, but I wonder if you can add your perspective 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, uh, even in celebration, right? Once, once COBIT hit, uh, we really saw that, uh, that, uh, in the 200 countries and territories that we operate in today and service our customers. And today that, uh, been a huge need, right? To send money, to support family, to support, uh, friends and loved ones across the world. And as part of that, uh, we, you know, we we're, we are, uh, very, uh, 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, uh, we, we did do some, uh, some the pivots and we did, uh, a solo rate, some of our plans on digital to help support that overall growth coming in there 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, 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, uh, really our part that our services come into play that, you know, we really support those families. So it was really a, a, a, a, 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, you were pushing the envelope too much in, in doing things with, with data or the technology that was just maybe too bold, maybe you felt like at some point it was, it was, 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, the varying 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 it's information. That's the way, how, how about Utah? We were talking earlier was sedation Cindy, about that bungee jumping moment. What can you share? Yeah. You know, I think you hit upon, uh, 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. This is that you need to be, need to feel comfortable being uncomfortable. I mean, that we have to be able to basically, uh, scale, right, expand and support that 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 what, uh, how you're operating today and your current business model, right. Things are only going to get faster. So you have to plan into align and to drive the actual transformation so that you can scale even faster in the future. So as part of that is 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, Cindy, 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, um, Dave, to answer your question, I would say the one bit of advice, maybe I was a little more, um, 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, as Tom and Gustavo said, get used to being uncomfortable, the power and politics are gonna happen. Break the rules, get used to that and be bold. Do not, 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 gonna go on to junk >>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 is 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, tremendous results. 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 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. So these please bring us home. Thank you. Thank you, Dave. Thank you. The cube team, and thanks. 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 make the positive change that you want to see happen when 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, Cindy 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 and apply that force, make sure your ideas are we start with talking about the importance of building consensus, not going at things all alone, sometimes building the importance of building the Koran. 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 sold 200 companies, 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 stock. And the last thing is these go to topspot.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've been up to since last year, we, 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 or engineers. All of those things will be available for you at hotspot beyond. Thank you. Thank you so much.

>>so, everyone. My name is Gustavo Canton. And thank you so much, Cindy, for the intro, as you mentioned doing transformations, Uh, it's ah, you know, high for Harry word situation. I have in power many transformations and I have let many transformations, And what I can tell you is that it's really hard to predict the future. But if you have ah, 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 evolved to evolve. And so in today, I'm gonna be talking about culture and data, and I'm gonna break this down in four areas. How do we get started? A barriers or opportunities, as I see it, the value of a I And also, how do you communicate? Especially now in the workforce off 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 the only what is happening in your function or your field. But you have to be very into what is happening. Society, socioeconomically speaking well being, you know, the common example is a good example, and for me personally is an opportunity, because the number one core value that I have is well being. I believe that for human potential, for customers and communities to grow well being should be at the center off every decision >>and, as somebody mentioned, is great to be, you know, staying tuned and have to excuse it and the courage. But for me personally, to be honest toe have this courage. It's not about not being afraid. You're always afraid when you're making big changes in 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 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, perhaps implications of my own self interest in my career, right, because you have to have that courage sometimes to make choices. There are no well saying, 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 studies in the past. And what they show is that if you look at the forming 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 Cindy has mentioned, this topic about culture is actually getting getting more and more traction. And in 2018 there was a study from HBR, and it was about 45%. I believe today is about 55%. 60% of respondents say that this is the main area that we need to be focusing 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 said a stay deadline to say, Hey, in two years, we're gonna make this happen. What do we need to do to empower and enable descent engines to make it happen? You need to make the tough choice. And so to me, when I speak about being bald, it's about making the right choices now. So I'll give examples of some of the roadblocks that I went through a side in the transformations, most recently a sin dimension, each neither. 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'll work in the past is not gonna work now. The opportunity there is that there is a lot of leaders who have a detail mindset, and they're open coming leaders that are perhaps not yet fully developed. We need to mentor those leaders and take bets on some of these telling, including young talent. >>We cannot be thinking in the past and just way for people you know, 3 to 5 years for them to develop because the world is going >>toe in a way that is super fast. The second area and this is specifically to implementation off a I. It is very interesting to me because just example that I have with gospel, right, we went on implementation and a lot of the way is the team functions of the leaders. Look at technology. They look at it from the prison, off the prior off success criteria for the traditional, the ice. And that's not gonna work again. The opportunity here is that you need to redefine what success looks like. In my case. I want the user experience off for work force. 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 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 covet, ah, lot of pressuring organizations and companies toe, you know, do more with less. And the solution that most leaders I see are taking is to just minimize cause. Sometimes in cut budget, we have to do the opposite. We have to actually invest in growth areas. But do it by business. Question. Don't do it by function if you actually invest and these kind of solutions if you actually invest on developing, you're telling your leadership to Seymour digitally. If you actually invest on fixing your data platform, it's not just an incremental cost. It's Actually this investment is gonna upset 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 weather. You might wanna work. So there is a lot of opportunity there just to put interest of perspective. They have in some studies in the past about, you know, how do we kind of measure the impact of data and obviously this is gonna vary by organization. Maturity is gonna is gonna 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 told him what I think it's interesting is they try to put attack line or attack price to what is the cause off? Incomplete data. So in this case, it's about 10 times as much to complete a unit for work when you have data that is flawed as supposed to have in 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 is going to cost you a dollar. So if you have perfect data, the total cost of that project maybe $100. But now let's say you have 80% perfect data and 20% flow data by using this assumption that flow data is 10 times as costly as perfect data. Your total cost now becomes $280 supposed to $100. This just for you to really think about as a CEO CEO, you know C h r o C E o. Are we really paying attention and really closing the gaps that we have former their infrastructure? If we don't do that, it's hard sometimes to >>see this noble 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 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 a love modeling and, you know, data and optimization here and >>all that stuff. That's what I came to analytics. But now, as a leader in a change agent, I need to speak about value. And in this case, for example, for Schneider, there was a spackling call, three of your energy. So the number one thing that they were asking from the analytics team waas actually efficiency, which to me was very interesting. But once I understood that, I understood what kind of language to use, how they're connected to the overall strategy and basically, how to bring in the the right leaders because you need toe, you know, focus on the leaders that you're gonna make the most progress. You know, again. >>No 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 a super simple for the, You know, 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 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, he waas about three years total transformation. But it waas two years for this component. Off augmented Alex. It took about two years to talk to, You know, I t get leadership, support, banking, budgeting, you know, get everybody on board, make sure this is sex criteria was correct. And we call this initiative people hundreds. I porta. 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 or 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 others just like you know, those. But 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 to. There are other many tools that you might have in your took it. But in my case, personally, I feel that you need tohave one portal going back to see this point that really, truly enabled 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 he 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 lady foundation, get the leadership and chasing cultures. So people can understand why you truly need to invest fundamental politics. And so what I'm showing here is an example off. How do we use basically, you know at all to capture in video the qualitative findings that we had, plus the quantitative insights that we have? So in this case or preliminary results, based on our ambition for three main metrics our safe user experience and adoption. So for our safe or ambition was to have 10 hours to be for employees safe 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. Can we? Per employee >>savings. I used to experience for 4.3 out of five and adoption of 50% really, really amazing work. But again, it takes a lot of collaboration for us to get to this stage from I t Legal communications. Obviously the operations things and the users, uh, in HR safety in other areas that might be basically stakeholders in this whole process. So, just to summarize, this kind of effort takes ah lot off 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 destruction happening, we don't have a choice. We have to >>take the risk, right. And in this case, I feel a lot off satisfaction in how we were able to gain all these very souls for this organization and acting 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 says to say thank you for everybody who has believed obviously in our vision, everybody who has believed in, you know, the world that we were trying to do and to make the life off are, you know, workforce or customers and community. Better as you can tell, there is a lot off 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 I just wanna tell for you If you are going right now, in a moment that you feel that you have to seem upstream. You know what With mentors. What with people in this in the industry that can help you out and guide you on this kindof transformation is not easy to do is high effort, but it is well worth it. And with that said, I hope you are well and it's been a pleasure talking to you activism tega.

>> 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.

>> Narrator: From theCube studios in Palo Alto in Boston, connecting with thought leaders all around the world, this is theCube Conversation. >> Hey, welcome back, everybody. Jeff Frick here with theCube. We're still on our Palo Alto studios, we're still getting through COVID and we're still doing all of our remotes, all of our interviews via remote and I'm really excited to have a guest we had around a long time ago. I looked it up is 2016, April 2016. She's Coco Brown, the founder and CEO of the Athena Alliance. Coco, it's great to see you. >> It's great to see you as well. We actually formally started in April of 2016. >> I know, I saw, I noticed that on LinkedIn. So we were at the Girls in Tech Catalyst Conference in Phoenix, I remembers was a really cool conference, met a ton of people, a lot of them have turned out that are on your board. So yeah, and you formally on LinkedIn, it says you started in May. So that was right at the very, very beginning. >> Yeah, that's right. >> So for people that aren't familiar with the at the Athena Alliance give them the quick overview. >> Okay. Well, it's a little different that it was four years ago. So Athena first and foremost is a digital platform. So you literally log in to Athena. And we're a combination of community access to opportunity and learning. And so you can kind of envision it a little bit like a walled garden around the LinkedIn, meets Khan Academy for senior executives, meets Hollywood agency for women trying to get into the boardroom and senior level roles in the c-suite as advisors, et cetera. And then the way that we operate is you can have a self-service experience of Athena, you can have a concierge experience with Athena with real humans in the loop making key connections for you and you can add accelerators where we build brand packages and BIOS and give you executive coaching. So... >> Wow. >> Kind of a... >> You've built out your services portfolio over the last several years. But still the focus >> yes, we have. is boards, right? Still the focus is getting women on public boards, or is that no longer still the focus? >> No, that's a big piece of it for sure. I mean, one of the things that we discovered, that was the very first mission of Athena, was to bring more women into the boardroom. And as we were doing that we discovered that once you get into a senior realm of leadership in general, there's more things that you want to do than just get into the boardroom. Some of it may be wanting to be an investor or an LP in a fund or become a CEO, or certainly join outside boards but also be relevant to your own inside board. And so we started to look at Athena as a more holistic experience for senior leaders who are attempting to make sure that they are the best they can be in this very senior realm of overarching stewardship of business. >> Awesome. and have you seen, so obviously your your focus shifted 'cause you needed to add more services based on the demand from the customers. But have you seen the receptiveness to women board members change over the last four years? How have you seen kind of the marketplace change? >> Yeah, it's changed a lot, I would say. First of all I think laws like the California law and Goldman Sachs coming out saying they won't take companies public unless they have diverse board data. The statements by big entities that people are paying attention to made the boardroom dynamics a conversation around the dinner table in general. So it became more of a common conversation and common interest as opposed to just the interest of a few people who are trying to get in there. And so that's created a lot of momentum as well as sort of thoughtfulness from leaders and from employees and from larger stakeholders to say the diversity at the top business has to mimic the demographics of society as a whole. And that's become a little bit more accepted as opposed to grudgingly sort of taken in. >> Right. So one of the big problems always it's like the VC problem, right? Is the whole matchmaking problem. How do you, how do qualified people find qualified opportunities? And I wonder if you can speak a little bit as to how that process has evolved, how are you really helping because there's always people that are looking for quality candidates, and there's great quality candidates out there that just don't know where to go. How are you helping bridge kind of that kind of basic matchmaking function? >> Yeah. I mean, there's a couple of different ways to go about it. One is certainly to understand and have real connections into the parts of the leadership ecosystem that influences or makes the decision as to who sits around that table. So that would be communities of CEOs, it's communities of existing board directors, it's venture capital firms, its private equity firms, and as you get really entrenched in those organizations and those ecosystems, you become part of that ecosystem and you become what they turn to to say, "Hey, do you know somebody?" Because it still is a "who do yo know" approach at the senior most levels. So that's one way. The other mechanism is really for individuals who are looking for board seats who want to be on boards to actually be thinking about how they proactively navigate their way to the kinds of boards that they would fit to. I like in a very much to the way our children go after the schools that they might want to when it's time for university. You'll figure out who your safeties, your matches, your reaches are, and figure out how you're going to take six degrees of separation and turn them into one through connections. So those are that's another way to go about it. >> You know, it's interesting, I talked to Beth Stewart from True Star, they also help place women on boards. And one of the issues is just the turnover. And I asked that just straight up, are there formal mechanisms to make sure that people who've been doing business from way before there were things like email and the internet eventually get swapped out. And she said, that's actually a big part of the problem is there isn't really a formal way to keep things fresh and to kind of rotate the incumbents out to enable somebody who's new and maybe has a different point of view to come in. So I'm curious when someone is targeting their A-list and B-list and C-lists, how do they factor in kind of the age of the board composition of the existing board, to really look for where there's these opportunities where a spot opens up, 'cause if there's not a spot open up clearly, there's really not much opportunity there. >> Yeah, I mean, you have to look at the whole ecosystem, right? I mean, there's anything from let's say series A, venture backed private companies all the way up to the mega cap companies, right? And there's this continuum. And it's not, there's not one universal answer to what you're talking about. So for example, if you're talking about smaller private companies, you're competing against, not somebody giving up their seat, but whether or not the company feels real motivation to fill that particular independent director seat. So the biggest competition is often that that seat goes unfilled. When you're talking about public companies, the biggest competition is really the fact that as my friend Adam Epstein of the small cap Institute will tell you, that 80% of public companies are actually small cap companies. And they don't have the same kinds of pressures that large caps do to have turnover. But yeah, it takes a big piece of the challenge is really boards having the disposition collectively to see the board as a competitive advantage for the business as a very necessary and productive piece of the business and when they see that then they take more proactive measures to make sure they have a evolving and strong board that does turnover as it needs to. >> Right. So I'm curious when you're talking to the high power women, right, who are in operational roles probably most of the time, how do you help coach them, how should they be thinking, what do they have to do different when they want to kind of add board seats to their portfolio? Very different kind of a role than an operational role, very different kind of concerns and day to day tasks. So, and clearly, you've added a whole bunch of extra things to your portfolio. So how do you help people, what do you tell women who say, "Okay, I've been successful, "I'm like successful executive, "but now I want to do this other thing, "I want to take this next step in my career"? What usually the gaps and what are the things that they need to do to prepare for that? >> Well, I'm going to circle in then land a little bit. Autodesk was actually a really great partner to us back when you and I first met. They had a couple of women at the top of the organization that were part of Athena, specifically because they wanted to join boards. They are on boards now, Lisa Campbell, Amy Bunszel, Debbie Clifford. And what they told us is they were experiencing everything that we were offering in terms of developing them, helping them to position themselves, understand themselves, navigate their way, was that they simply became better leaders as a result of focusing on themselves as that next level up, irrespective of the fact that it took them two to three years to land that seat. They became stronger in their executive role in general and better able to communicate and engage with their own boards. So I think, now I'm landing, the thing that I would say about that is don't wait until you're thinking oh, I want to join a board, to do the work to get yourself into that ecosystem, into that atmosphere and into that mindset, because the sooner you do that as an executive, the better you will be in that atmosphere, the more prepared you will be. And you also have to recognize that it will take time. >> Right. And the how has COVID impacted it, I mean, on one hand, meeting somebody for coffee and having a face to face is a really important part of getting to know someone and a big part of I'm sure, what was the recruitment process, and do you know someone, yeah, let's go meet for a cup of coffee or dinner or whatever. Can't do that anymore, but we can all meet this way, we can all get on virtually and so in some ways, it's probably an enabler, which before you could grab an hour or you didn't have to fly cross-country or somebody didn't have to fly cross-country. So I'm kind of curious in this new reality, which is going to continue for some time. How has that impacted kind of people's ability to discover and get to know and build trust for these very very senior positions. >> HBR just came out with a really great article about the virtual board meeting. I don't know if you saw it but I can send you a link. I think that what I'm learning from board directors in general and leaders in general is that yes, there's things that make it difficult to engage remotely, but there's also a lot of benefit to being able to get comfortable with the virtual world. So it's certainly, particularly with COVID, with racial equity issues, with the uncertain economy, boards are having to meet more often and they're having, some are having weekly stand ups and those are facilitated by getting more and more comfortable with being virtual. And I think they're realizing that you don't have to press flesh, as they say, to actually build intimacy and real connection. And that's been a hold up, but I think as the top leadership gets to understand that and feel that for themselves, it becomes easier for them to adopt it throughout the organization that the virtual world is one we can really embrace, not just for a period of time. >> It's funny we had John Chambers on early on in this whole process, really talking about leadership and leading through transition. And he used the example, I think had been that day or maybe a couple days off from our interview where they had a board meeting, I think they were talking about some hamburger restaurant, and so they just delivered hamburgers to everybody's office and they had the board meeting. But that's really progressive for a board to actually be doing weekly stand ups. That really shows a pretty transformative way to manage the business and kind of what we think is the stodgy old traditional get together now and then, fly and then get some minutes and fly out, that's super progressive. >> Yeah. I mean, I was on three different board meetings this week with a company I'm on the board of in Minnesota. And we haven't seen each other in person in, I guess since January. (woman laughs) >> So final tips for women that want to make this this move, who, they've got some breathing space, they're not homeschooling the kids all day while they're trying to get their job done and trying to save their own business, but have some cycles and the capabilities. What do you tell them, where should they begin, how should they start thinking about, kind of taking on this additional responsibility and really professional growth in their life? >> Well, I mean, I think something very important for all of us to think about with regard to board service and in general as we get into a very senior level point in our careers at a managing and impact portfolio. People get into a senior point and they don't just want to be an executive for one company, they want to have a variety of ways that they're delivering impact, whether it's as an investor or as a board member or as other things as well as being an operator. And I think the misnomer is that people believe that you have to add them up and they, one plus one plus one equals three, and it's just not true. The truth is that when you add a board seat, when you add that other thing that you're doing it makes you better as a leader in general. Every board meeting I have with [Indistinct] gives me more than I bring back to Athena as an example. And so I think we tend to think of not being able to take on one more thing and I say that we all have a little more space than we think we have to take on the things we want to do. >> Right? That's a good message to me. It is often said if you want to get something done, give it to the busiest person in the room. It's more likely to get it done 'cause you got to be efficient and you just have that kind of get it done attitude. >> That's right. >> All right, Coco. Well, thank you for sharing your thoughts. >> Congratulations, so I guess it's your four year anniversary, five year anniversary [Indistinct] about right? >> Yes, four. >> That's terrific. And we look forward to continuing to watch the growth and hopefully checking in face to face at some point in the not too distant future. >> I would like that. >> All right. Thanks a lot Coco. >> Great talking to you. >> Already. >> She's Coco, I'm Jeff. You're watching theCube. Thanks for watching, we'll see you next time. (upbeat music)

>>LA Las Vegas. It's the cube hovering AWS reinvent 2019 brought to you by Amazon web services and along with its ecosystem partners. >>Hey, welcome back to the cube. Our day one coverage of AWS reinvent 19 continues. Lisa Martin with Dave Volante. Dave and I have a couple of guests we'd like you to walk up. We've got Anthony Brooks billions, the CEO of HBR back on the cube. You're alumni. We should get you a pin and snowflake alumni. But Chris, your new Chris Dagon, chief revenue officer from snowflake. Chris, welcome to the program. Excited to be here. All right guys. So even though both companies have been on before, Anthony, let's start with you. Give our audience a refresher about HVR, who you guys are at, what you do. >>Sure. So we're in the data integration space, particularly a real time data integration. So we move data to the cloud in the in the most efficient way and we make sure it's secure and it's accurate and you're moving into environments such as snowflake. Um, and that's where we've got some really good customers that we happy to talk about joint custody that we're doing together. But Chris can tell us a little bit about snowflake. >>Sure. And snowflake is a cloud data warehousing company. We are cloud native, we are on AWS or on GCP and we're on Azure. And if you look at the competitive landscape, we compete with our friends at Amazon. We compete with our friends at Microsoft and our friends at Google. So it's super interesting place to be, but it very exciting at the same time and super excited to partner with Anthony and some others who aren't really a friends. That's correct. So I wonder if we could start by just talking about the data warehouse sort of trends that you guys see. When I talk to practitioners in the old days, they used to say to me things like, Oh, infrastructure management, it's such a nightmare. It's like a snake swallowing a basketball every time until it comes out with a new chips. We chase it because we just need more performance and we can't get our jobs done fast enough. And there's only three. There's three guys that we got to go through to get any answers and it was just never really lived up to the promise of 360 degree view of your business and realtime analytics. How has that changed? >>Well, there's that too. I mean obviously the cloud has had a big difference on that illustrious city. Um, what you would find is in, in, in yesterday, customers have these, a retail customer has these big events twice a year. And so to do an analysis on what's being sold and Casper's transactions, they bought this big data warehouse environment for two events a year typically. And so what's happening that's highly cost, highly costly as we know to maintain and then cause the advances in technology and trips and stuff. And then you move into this cloud world which gives you that Lester city of scale up, scale down as you need to. And then particular where we've got Tonies snowflake that is built for that environment and that elicited city. And so you get someone like us that can move this data at today's scale and volume through these techniques we have into an environment that then bleeds into helping them solve the challenge that you talk about of Yesi of >>these big clunky environments. That side, I think you, I think you kind of nailed it. I think like early days. So our founders are from Oracle and they were building Oracle AI nine nine, 10 G. and when I interviewed them I was the first sales rep showing up and day one I'm like, what the heck am I selling? And when I met them I said, tell me what the benefit of snowflake is. And they're like, well at Oracle, and we'd go talk to customers and they'd say, Oracles, you know, I have this problem with Oracle. They'd say, Hey, that's, you know, seven generations ago were Oracle. Do you have an upgraded to the latest code? So one of the things they talked about as being a service, Hey, we want to make it really easy. You never have to upgrade the service. And then to your point around, you have a fixed amount of resources on premise, so you can't all of a sudden if you have a new project, do you want to bring on the first question I asked when I started snowflake to customers was how long does it take you to kick off a net new workload onto your data, onto your Vertica and it take them nine to 12 months because they'd have to go procure the new hardware, install it, and guess what? >>With snowflake, you can make an instantaneous decision and because of our last test city, because the benefits of our partner from Amazon, you can really grow with your demand of your business. >>Many don't have the luxury of nine to 12 months anymore, Chris, because we all know if, if an enterprise legacy business isn't thinking, there's somebody not far behind me who has the elasticity, who has the appetite, who's who understands the opportunity that cloud provides. If you're not thinking that, as auntie Jessie will say, you're going to be on the wrong end of that equation. But for large enterprises, that's hard. The whole change culture is very hard to do. I'd love to get your perspective, Chris, what you're seeing in terms of industries shifting their mindsets to understand the value that they could unlock with this data, but how are big industries legacy industries changing? >>I'd say that, look, we were chasing Amad, we were chasing the cloud providers early days, so five years ago, we're selling to ad tech and online gaming companies today. What's happened in the industry is, and I'll give you a perfect example, is Ben wa and I, one of our founders went out to one of the largest investment banks on wall street five years ago, and they said, and they have more money than God, and they say, Hey, we love what you've built. We love, when are you going to run on premise? And Ben, Ben wa uttered this phrase of, Hey, you will run on the public cloud before we ever run in the private cloud. And guess what? He was a truth teller because five years later, they are one of our largest customers today. And they made the decision to move to the cloud and we're seeing financial services at a blistering face moved to the cloud. >>And that's where, you know, partnering with folks from HR is super important for us because we don't have the ability to just magically have this data appear in the cloud. And that's where we rely quite heavily on on instance. So Anthony, in the financial services world in particular, it used to be a cloud. Never that was an evil word. Automation. No, we have to have full control and in migration, never digital transformation to start to change those things. It's really become an imperative, but it's by in particular is really challenging. So I wonder if we could dig into that a little bit and help us understand how you solve that problem. >>Yes. A customer say they want to adopt some of these technologies. So there's the migration route. They may want to go adopt some of these, these cloud databases, the cloud data warehouses. And so we have some areas where we, you know, we can do that and keep the business up and running at the same time. So the techniques we use are we reading the transactional logs, other databases or something called CDC. And so there'll be an initial transfer of the bulk of the data initiative stantiating or refresh. At that same time we capturing data out of the transaction logs, wildlife systems live and doing a migration to the new environment or into snowflakes world, capturing data where it's happening, where the data is generated and moving that real time securely, accurately into this environment for somewhere like 1-800-FLOWERS where they can do this, make better decisions to say the cost is better at point of sale. >>So have all their business divisions pulling it in. So there's the migration aspects and then there's the, the use case around the realtime reporting as well. So you're essentially refueling the plane. Well while you're in mid air. Um, yeah, that's a good one. So what does the customer see? How disruptive is it? How do you minimize that disruption? Well, the good thing is, well we've all got these experienced teams like Chris said that have been around the block and a lot of us have done this. What we do, what ed days fail for the last 15 years, that companies like golden gate that we sold to Oracle and those things. And so there's a whole consultative approach to them versus just here's some software, good luck with it. So there's that aspect where there's a lot of planning that goes into that and then through that using our technologies that are well suited to this Appleton shows some good success and that's a key focus for us. And in our world, in this subscription by SAS top world, customer success is key. And so we have to build a lot of that into how we make this successful as well. >>I think it's a barrier to entry, like going, going from on premise to the cloud. That's the number one pushback that we get when we go out and say, Hey, we have a cloud native data warehouse. Like how the heck are we going to get the data to the cloud? And that's where, you know, a partnership with HR. Super important. Yeah. >>What are some of the things that you guys encountered? Because we many businesses live in the multi-cloud world most of the time, not by strategy, right? A lot of the CIO say, well we sort of inherited this, or it's M and a or it's developers that have preference. How do you help customers move data appropriately based on the value that the perceived value that it can give in what is really a multi world today? Chris, we'll start with you. >>Yeah, I think so. So as we go into customers, I think the biggest hurdle for them to move to the cloud is security because they think the cloud is not secure. So if we, if you look at our engagement with customers, we go in and we actually have to sell the value snowflake and then they say, well, okay great, go talk to the security team. And then we talked to security team and say, Hey, let me show you how we secure data. And then then they have to get comfortable around how they're going to actually move, get the data from on premise to the cloud. And that's again, when we engage with partners like her. So yeah, >>and then we go through a whole process with a customer. There's a taking some of that data in a, in a POC type environment and proving that after, as before it gets rolled out. And a lot of, you know, references and case studies around it as well. >>Depends on the customer that you have some customers who are bold and it doesn't matter the size. We have a fortune 100 customer who literally had an on premise Teradata system that they moved from on prem, from on premise 30 to choose snowflake in 111 days because they were all in. You have other customers that say, Hey, I'm going to take it easy. I'm going to workload by workload. And it just depends. And the mileage may vary is what can it give us an example of maybe a customer example or in what workloads they moved? Was it reporting? What other kinds? Yeah. >>Oh yeah. We got a couple of, you mean we could talk a little bit about 1-800-FLOWERS. We can talk about someone like Pitney Bowes where they were moving from Oracle to secret server. It's a bunch of SAP data sitting in SAP ECC. So there's some complexity around how you acquire, how you decode that data, which we ever built a unique ability to do where we can decode the cluster and pool tables coupled with our CDC technique and they had some stringent performance loads, um, that a bunch of the vendors couldn't meet the needs between both our companies. And so we were able to solve their challenge for them jointly and move this data at scale in the performance that they needed out with these articles, secret server enrollments into, into snowflake. >>I almost feel like when you have an SAP environment, it's almost stuck in SAP. So to get it out is like, it's scary, right? And this is where it's super awesome for us to do work like this. >>On that front, I wanted to understand your thoughts on transformation. It's a word, it's a theme of reinvent 2019. It's a word that we hear at every event, whether we're talking about digital transformation, workforce, it, et cetera. But one of the things that Andy Jassy said this morning was that got us start. It's this is more than technology, right? This, the next gen cloud is more than technology. It's about getting those senior leaders on board. Chris, your perspective, looking at financial services first, we were really surprised at how quickly they've been able to move. Understanding presumably that if they don't, there's going to be other businesses. But are you seeing that as the chief revenue officer or your conversations starting at that CEO level? >>It kinda has to like in the reason why if you do in bottoms up approach and say, Hey, I've got a great technology and you sell this great technology to, you know, a tech person. The reality is unless the C E O CIO or CTO has an initiative to do digital transformation and move to the cloud, you'll die. You'll die in security, you'll die in legal lawyers love to kill deals. And so those are the two areas that I see D deals, you know, slow down significantly. And that's where, you know, we, it's, it's getting through those processes and finding the champion at the CEO level, CIO level, CTO level. If you're, if you're a modern day CIO and you do not have a a cloud strategy, you're probably going to get replaced >>in 18 months. So you know, you better get on board and you'd better take, you know, taking advantage of what's happening in the industry. >>And I think that coupled with the fact that in today's world, you mean, you said there's a, it gets thrown around as a, as a theme and particularly the last couple of years, I think it's, it's now it is actually a strategy and, and reality because what Josephine is that there's as many it tech savvy people sit in the business side of organizations today that used to sit in legacy it. And I think it's that coupled with the leadership driving it that's, that's demanding it, that demanding to be able to access that certain type of data in a geo to make decisions that affect the business. Right now. >>I wonder if we could talk a little bit more about some of the innovations that are coming up. I mean I've been really hard on data. The data warehouse industry, you can tell I'm jaded. I've been around a long time. I mean I've always said that that Sarbanes Oxley saved the old school BI and data warehousing and because all the reporting requirements, and again that business never lived up to its promises, but it seems like there's this whole new set of workloads emerging in the cloud where you take a data warehouse like a snowflake, you may be bringing in some ML tools, maybe it's Databricks or whatever. You HVR helping you sort of virtualize the data and people are driving new workloads that are, that are bringing insights that they couldn't get before in near real time. What are you seeing in terms of some of those gestalt trends and how are companies taking advantage of these innovations? >>I think one is just the general proliferation of data. There's just more data and like you're saying from many different sources, so they're capturing data from CNC machines in factories, you know like like we do for someone like GE, that type of data is to data financial data that's sitting in a BU taking all of that and going there's just as boss some of data, how can we get a total view of our business and at a board level make better decisions and that's where they got put it in I snowflake in this an elastic environment that allows them to do this consolidated view of that whole organization, but I think it's largely been driven by things that digitize their sensors on everything and there's just a sheer volume of data. I think all of that coming together is what's, what's driven it >>is is data access. We talked about security a little bit, but who has rights to access the data? Is that a challenge? How are you guys solving that or is it, I mean I think it's like anything like once people start to understand how a date where we're an acid compliant date sequel database, so we whatever your security you use on your on premise, you can use the same on snowflake. It's just a misperception that the industry has that being on, on in a data center is more secure than being in the cloud and it's actually wrong. I guess my question is not so much security in the cloud, it's more what you were saying about the disparate data sources that coming in hard and fast now. And how do you keep track of who has access to the data? I mean is it another security tool or is it a partnership within owes? >>Yeah, absolutely man. So there's also, there's in financial data, there's certain geos, data leaves, certain geos, whether it be in the EU or certain companies, particularly this end, there's big banks now California, there's stuff that we can do from a security perspective in the data that we move that's secure, it's encrypted. If we capturing data from multiple different sources, items we have that we have the ability to take it all through one, one proxy in the firewall, which does, it helps him a lot in that aspect. Something unique in our technology. But then there's other tools that they have and largely you sit down with them and it's their sort of governance that they have in the, in the organization to go, how do they tackle that and the rules they set around it, you know? >>Well, last question I have is, so we're seeing, you know, I look at the spending data and my breaking analysis, go on my LinkedIn, you'll see it snowflakes off the charts. It's up there with, with robotic process automation and obviously Redshift. Very strong. Do you see those two? I think you addressed it before, but I'd love to get you on record sort of coexisting and thriving. Really, that's not the enemy, right? It's the, it's the Terra data's and the IBM's and the Oracles. The, >>I think, look, uh, you know, Amazon, our relationship with Amazon is like a, you know, a 20 year marriage, right? Sometimes there's good days, sometimes there's bad days. And I think, uh, you know, every year about this time, you know, we get a bat phone call from someone at Amazon saying, Hey, you know, the Redshift team's coming out with a snowflake killer. And I've heard that literally for six years now. Um, it turns out that there's an opportunity for us to coexist. Turns out there's an opportunity for us to compete. Um, and it's all about how they handle themselves as a business. Amazon has been tremendous in separation of that, of, okay, are going to partner here, we're going to compete here, and we're okay if you guys beat us. And, and so that's how they operate. But yes, it is complex and it's, it's, there are challenges. >>Well, the marketplace guys must love you though because you're selling a lot of computers. >>Well, yeah, yeah. This is three guys. They, when they left, we have a summer thing. You mean NWS have a technological DMS, their data migration service, they work with us. They refer opportunities to us when it's these big enterprises that are use cases, scale complexity, volume of data. That's what we do. We're not necessary into the the smaller mom and pop type shops that just want to adopt it, and I think that's where we all both able to go coexist together. There's more than enough. >>All right. You're right. It's like, it's like, Hey, we have champions in the Esri group, the EEC tuna group, that private link group, you know, across all the Amazon products. So there's a lot of friends of ours. Yeah, the red shift team doesn't like us, but that's okay. I can live in >>healthy coopertition, but it just goes to show that not only do customers and partners have toys, but they're exercising it. Gentlemen, thank you for joining David knee on the key of this afternoon. We appreciate your time. Thank you for having us. Pleasure our pleasure for Dave Volante. I'm Lisa Martin. You're watching the queue from day one of our coverage of AWS reinvent 19 thanks for watching.

(upbeat bright music) >> From our studios, in the heart of Silicone Valley, Palo Alto, California. This is a Cube Conversation. >> Hey, welcome back everybody. Jeff Frick here with The Cube. We are having a Cube Conversation here in the studio. We're just about ready to hit the crazy wave that is the conference season. So, it's great to still have some time to do some studio stuff before we hit the road. And we're excited to have a new guest that's never been on the cube before. He is Daniel Hazarika, the CMO of Reflektive. Daniel, great to meet you. >> Great to meet you. >> So, you guys are working in the cool space. Kind of the new age, HR management for lack of a better term. We've had Patty Mccord on before, who obviously was seminal in kind of the Netflix culture. Which was, I think, pretty early days and kind of saying throw out, throw out traditional annual reviews. Kind of, throw out regulations around expense reports. Throw out, kind of, a lot of these traditional mechanisms to manage people and really say, you know, what are we managing people to? And we should be giving them feedback on a regular basis, and we really need to, kind of, bring this into the modern era. And that's smack in the middle of what you guys do. >> Absolutely, yeah. I mean a big part of what we do is managing employees to be high performing. And that's the big tagline for her, is high performance culture. >> Right. >> It's critical to have, as part of that, a more active and ongoing role with your employees. That's why they can do things like remove expense report guidelines. Because they know we're on the pulse of whether this person is actually performing or not. And, by knowing that, we can have faith that they're, we trust them. That they'll do the right thing when it comes to deciding on what they spend on. >> Right. >> So, I think we sit right at the center of this and we're really excited to be a part of it. >> So, let's back up a little bit and just give everyone kind of the 411 on Reflektive. >> Absolutely. >> How many people are you? How long you've been around? >> Yeah. >> Some of the basics. >> Yeah. So, we were founded in late 2014. We have 3 co-founders; Rajeev Behera, Erick Tai, and Jimmy Tyrrell. They more or less were actually people managers themselves. They realized this was a gap in, you know, in managing work forces and, you know, classic model of technical founder and then more of a product person and then they got together and built this really cool tool. >> So what was the big hole? Cause there's are a ton of HR applications out there. >> Absolutely. >> There's big ones likes Workday, you know, whose done been very successful on the SaaS Model. What did they see that was the big hole even though there's all these huge traditional kind of HR applications? >> Absolutely, yeah. So, what happened was, there is a fivish year-old Berson framework, they talk about this systems of engagement and systems of record, right? >> Right. >> And so these tools that you mention that were great at helping catalogue what happens in a business, and do all the compliance processes required, right? But what happened was the world changed. Things, in terms of social media, the way people were getting information, the pace of things accelerated quite a bit and these tools struggled to handle the day to day. And didn't live where people worked. And, those are big gaps. So, they saw this and said, okay, well there is something here where we can go in and insert ourselves in the flow of people's work and help them actually get the information they need to be high performing. >> So, was the entry point the annual review? What was kind of the entry point >> Yeah. >> To get people to think about HR in a different way and to adopt the technology? >> Yeah. >> I think, I think that ultimately there is some form of review that happens and they built that functionality. But, what was really interesting to the market was that actually the concept of real time feedback and the mechanisms, building the mechanisms, by which you could actually bring that into that platform. And actually factor that in when you're doing reviews, right? There's, this eliminates things like recency bias things that, hey a review is happening at the end of the year, I'm going to remember what happened the last 3 months. I'm not going to remember that you killed it, you know, in March of that year. So, we're helping solve for that. And they've saw great results doing that. >> Right. So, you've got all types of kind of little, I don't know apps is the right word >> Sure. >> Solutions. Or, you know, kind of activities that enable people both as the employee as well as the manager as well as the HR people to have kind of this ongoing back and forth relationship. So, I was wondering if you could dive into some of those applications and what's, what's working really well that's different than things used to be? >> Yeah. So, the modern kind of version of what we do, cause things have changed much over the past few years, we have a core kind of performance management offering. We also have an engagement offering and we also have a people intelligence offering. And these are the three pillars by which we kind of enable all those people that you just talked about. And so, when we go back to the performance piece, there's many different components, but, we believe that employees need feedback in the moment. They need a way to also do annual reviews. They need a way to set goals and be clear with their manager on what those are and what progress is. And we also believe that those things have to exist in the flow of day to day work and that's why do things like have a Slack integration, integrate with Gmail, Outlook, all these different kind of places where people actually live day to day. >> Right. >> Then, you know, the other layers that I spoke about are engagement. We like to be able to do broad surveys to companies and, you know, get a pulse on high level, what is the emotion out there? How are people feeling about management? How are people feeling about, you know, even the snacks in the kitchen? Simple stuff like that. >> Right. >> And, then last but not least, all of that information has to feed into somewhere so that the management of an organization can get the insights they need to make decisions. And that's where the people intelligence comes in. >> Okay, this is a lot of different layers to the story. But the one that, when I was first preparing for this interview, and like, oh my goodness, another tool, right? >> Right, yeah. >> Another desktop app. I forget what the statistics are of all the tabs that we have open >> Yeah. >> With our Salesforce and Outlook and all these things are open. But, you guys took an interesting approach, 'cause you actually integrated with some of the apps that you presume I have open like Slack as opposed to, you know, kind of forcing me to have that one more tab. How does that work and how has that, you know, kind of impacted adoption? >> Totally yeah. This is where the foundations of our company kind of come into play. So, our founders came from Mobile Applications. They knew, and games specifically, so they know how to optimize for things like active users daily, monthly, all that, right? And, taking that lens to it, they said, okay, we really do need to encourage adoption. How do we make that happen? To your point, too many tools are open. Some are required to do your job like email. Others are kind of optional. We're, we're, you know, honest with ourselves. We say, hey, we're in the optional category. How do we solve for that? How do we still get people to use this? So, we said, we're going to plug ourselves into Slack where people actually communicate day to day. We're going to show up in Gmail. We're going to show up in Outlook. We're going to go to all these different places where people are already working. We actually even integrate with Jira, the engineering tool. And we said, that's the way we'll actually get the information into our system that we need, and then we can service all those insights that we talked about. >> Is it like a, is it a pop-up? Is it some encouragement when I do some activity say, say with you on a project, you know, oh Jeff, by the way, do you have any feedback for Daniel? Or, oh Jeff, by the way, somebody's looking for feedback on Daniel. Or, I mean, how does the mechanics work and, then, what have you seen in terms of adoption what works, what doesn't work? >> Yeah. I mean, it definitely gets traction. Because, I think, specifically Slack, and, you know, we're a Silicon Valley company, a lot of our earlier customers were Silicon Valley companies, and they all use Slack. It's pretty >> As do we. >> Yeah. There you go, right? So, I think from that perspective it's really easy to use. You can see all the active recognition, for example, happening in your company. And, in channel, you can also go in and input recognition for other people right there just at mention and, kind of, invoke that. >> So, are they kind of channels then within Slack, around? >> Recognition can be a channel but the actual input of feedback you can do that right from the keyboard, yeah. >> So, interesting, talk about feedback versus recognition. How does that play out in the real world? Cause those are two very different words and two different, very different motivations. >> You bring up a great, great point and it's in an ongoing debate, like how do you, kind of, name these two different things? Frankly, recognition, to the broader market, ends up being more or less positive feedback, right? That you feel like you want to put a public stamp on. >> Right. >> But, there's an important distinction here because there's also negative feedback and there's also just feedback that people want to give that's positive but they don't necessarily want to share that with the entire world, or with the broader organization. So, we wanted to create a safe space for them to be able to do that at every single, in every single use case. And, so, that's what, that's where the delineation between recognition and feedback comes in is that you can go public, private, you know, public and also broadcast to the whole company. And we wanted to give people the avenue to do all those things. >> Right. So, I want to shift gears a little bit and talk about goals and goal management. How does that kind of module work and/or how does that tie back to, kind of, some of the corporate goals and corporate initiatives? Can you tie it back to your project and are these things integrated or is it, kind of, a stand-alone? Does it operate like an annual goal or a quarterly goal or, you know, how does that piece of it work? >> Yeah. So, the way that we find, you know, the highest performance cultures doing this, they do, kind of, adjust goals on an ongoing basis. Ideally quarterly. I think that's probably the favored, kind of, happy medium right now. >> Okay. >> And, that does start with company level goals, then it goes to departmental, then it goes to individual or team, sub-team, goals. And, all of these people have, you know, we can call, you can do SMART goals, you know, you can do objectives and key results. You can do whatever format you want and it's pretty flexible as a platform but all of that cascades down and you can go work, you know, coordinate between people and get visibility. You can have public goals, private goals and that's part of our whole commitment to transparency in the platform. >> In terms of your customers, and their adoption at a corporate level, not necessarily the individual, is it more of a stick or is it more of carrot? Are people figuring out that they need to change and yours is the tool to give them an avenue to the new way? Or, is it kind of new and provocative and, we've been doing annual reviews since, since my dad's dad's dad, you know, I'm not quite sure about this ongoing thing. What's kind of the reception and how's the market changing? >> Totally. Like with anything, you know, either tech adoption or lifecycle, a lot of our early adopters have just picked up on the fact that the market for talent is extremely competitive now. And some have got to different maturity levels in understanding what they need to do to deal with that, right? Our earliest adopters, they just got it right away. They said, like, we, our workforce is asking for more in the moment feedback. They want to know what their goals are clearly and be able to measure against them and be able to go and point back, hey, I actually achieved that, or I did not. And, so, that has helped us a lot with the earlier adopters. Just saying, like, we built something that's ideally suited to what you need, they way you need to evolve. >> Right. >> Part of, I mean, the task of any kind of innovative technology is we have to go educate the market too. We know that universally people are struggling to retain talent. What we do to educate them is to inform them of, here's actually what the workforce is looking for. We've done a ton of research. HBR articles, we've seen Gallup Research, we've seen all sorts of stuff that tells you the world has changed, the workforce is expecting certain things, and we've built something around those needs. >> Right. >> And, so, the more we do our job as marketing, you know, to make sure the market understands that, I think the more Reflektive will see success. >> It's funny in one of Patty's recent media posts, she talks about foosball tables and billiard tables, like, that's not what drives employee happiness and satisfaction. I mean, they look good, I guess, on the tour before you take the job but, I don't know, there's a lot of other things that drive happiness and retention in this super competitive market. That's not the ping pong table. >> Absolutely. Especially in the case of Patty McCord, I mean, she's indexing everything around, you want to have the highest performing people stay and you don't necessarily care to actively manage the ones who are not. And what she has, you know, espoused many times is that, when, the highest performing people actually love this. They love that there's transparency around the business value they're driving. They love to know exactly where they stand. They love to have feedback so they can improve and be better. And, so, you can see how there's a lot of, like, parallels here between what's she's talking about that high performing cultures do and what the platform that we've built enables. >> Right. What about the pesky lawyers that are saying there are all these compliance issues and we're still, we're still operating off of laws that were established before and this is a little bit funky and we're not really sure how to deal with it? >> Yeah. I mean, what we've actually found is, so, there's specific customers, even of the size of Airbnb, who will highlight that we helped them combat bias. And the way we do this, and evidence that they are not biased in the way they do reviews, and the way we do this is, I think the concept, is ultimately the concept of real time feedback. Because this stuff is being logged as it's happening, no one can say, oh, it's the end of the year now and you just remember what happened in the past few months, you're ignoring all my great, you know, all my great work that happened before that. This is not fair, You know, that recency bias they call it, is eliminated. >> And that actually, in the end, helps with the lawyers because we can say, this was all cataloged in the moment as opposed to way later. >> Right. We have to train among contract to your concept. You're supposed to turn it up the last month. So, they forget about the crappy stuff that you did earlier in the year. >> Exactly. >> And do well. So, Dan, before I let you go, just, you've been around a little while, you've been in the Valley, you've been at a number of startups, you've been here for about a year, I'm just curious, kind of, as you've come to Reflektive and been there now, what was the biggest surprise, kind of, entering this space, entering this company that you didn't necessarily expect now that you've been there for a little bit? >> Yeah. I think what was most interesting, actually kind of exciting, was to observe how similar the transformation that HR is going through right now is to the transformation that marketing went through ten years ago. I'm seeing the movement to being more data driven, to getting active information on how campaigns are running, all this stuff. That evolution is happening in HR right now. I'm seeing, you know, more and more people scientists. I'm seeing more and more people who are turning people management into a science. And, I think that a lot it has to do with record low unemployment. The market for labor got so competitive that people have started really paying attention to this as a problem and trying to understand better outside of just simple compliance things. How can we actually actively manage our workforce into being high performing and happier. That's really interesting for me. >> Awesome. Well, thanks for taking a few minutes out of your day and sharing your story. >> Absolutely. >> Alright. He's Daniel, I'm Jeff. You're watching the Cube. We're having a Cube Conversation at our Palo Alto studios. We'll see you next time. Thanks for watching. (exciting music)

(upbeat music) >> Live from San Francisco, it's theCUBE covering Google Cloud Next 2018, brought to you by Google Cloud, and it's Ecosystem Partners. >> Hello everyone, and welcome back theCUBE live coverage, here in San Francisco, the Moscone South. I'm John Furrier with the SiliconANGLE on theCube, with my cohost Dave Vellante, for next three days. Day one, wrap up of Google Next here. Google Cloud's premiere event. This is a different Google. It's a world changing event, in my opinion, of Google. Dave, I want to analyze day one as we put it in the books. Let's analyze and let's look at it, and critique and observe the moves that Google's making vis-à-vis the competition. And Diane Greene, who's on theCUBE earlier, great guest. Kind of in her comfort zone here on theCUBE because she talks, she's an engineer, she's super smart. She thinks free thoughts but she really has a good chessboard view of the landscape. My big walk away today is that she's got full command of what she wants to do, but she's in an uncomfortable position that I think she's not used to. And that is at VMworld, at VMware, she didn't have competition. First mover, changes the market. Certainly, winning at all fronts when VMware was starting. And they morphed over and then you know the history of Vmware: sold to EMC and then now the rest is history. But they really changed the category. They created a category. And were very successful in IT with virtual machines. She's got competition in Cloud. She's playing from behind. She's got the big guns. She's going to bring out the howitzers, you know? I mean she's got Spanner, BigQuery, all the Scale, Kubernetes. Which the internal name is Borg which has been running on the Google infrastructure. Provisioning services on all their applications with billions and billions of users. If she can translate that, that's key. So that's one observation. And the second one is that Google is taking a data centric view. Their competitive advantage is dealing with data. And if you look at everything that they're doing from TensorFlow for AI and all the themes here. They are positioning Google as with a place to bring your data. Okay, that is clear to me as a stake in the ground. With the large scale technical infrastructure they're going to roll out with SREs. Those two things to me are the front and center major power moves that they're making. The rest wrapping around it is Kubernetes, Istio, a service oriented architecture managing services not products and providing large scale value to their customers that don't want to be Google. They want to be like Google in the benefits of Scale, which comes in automation. And I think I head room for Google Cloud is IT operations. So that's kind of like my take. I think day one, the people we've had on from Google sharp as nails, no enterprise tech. Jennifer Lin, Deepti, Diane Greene. The list goes on and on. What's your take? >> Well so, first of all with what's goin' on here and Diane Greene, the game she's playing now. Completely different obviously than VMware. Where it was all about cutting costs. Vmware, when you think about it, sold for $635 million to EMC way back when. So, it was just a little scratch compared to what we're talkin' about now. She didn't have the resources. The IT business, you remember Nick Carr's famous piece on HBR 'Does IT Matter?' That was the sentiment back then. IT, waste of time, undifferentiated. Just cut costs. Cut, cut, cut. Perfect for Vmware. The game they're playing now is totally different. As you said they were late to the enterprise. Ironically, late to the "enterprise cloud" >> They got competition >> They got competition. Obviously the two big ones Microsoft and, of course, AWS. But so what might take away here is: the differentiation. So they're not panicking. They're obviously playing the open source card. Kubernetes, TensorFlow, etc. Giving back to the community. Data, they're definitely going to lead in AI and machine intelligence. No question about it. So they're going to play that card. The database, we had the folks from Cloud Spanner on today. Amazing technology. Where as you think about it, they're talkin' about a transaction-oriented database. We heard a customer today, talking about we replaced Oracle. Right? We got rid of Oracle, now-- >> When was the last time you heard that? Not many times. >> It's not often. No, and they're only $120 million company. But to her point was it's game changing for us. It's a 10-X value proposition. And we're getting the same quality that we're getting out of our Oracle databases. They're leading with apps on Google Cloud. Twitter is there. Spotify. They obviously have a lot of history. So that's part of it, part to focus. We on SiliconANGLE.com, there's a great article by Mark Albertson. He talked about the-- he compared the partner Ecosystem. Google's only about 13,000 partners. Amazon 100,000. Azure 70,000. So a long way to go there. Serverless, this is they're catching up on serverless. But they're still behind. Kind of still in Beta, right? &But serverless, John, I'd love your take on this. Can be as profound as virtualization was. Last to developer love. They've got juice with developers. And then the technology. Massive scale. We heard things about Spanner, the relational semantics. BigQuery, Kubernetes, TensorFlow. They have this automate or die culture. You talked about this in your article. That's a bottoms-up engineering culture. Much different than the traditional enterprise top-down "Go take that hill! "You're going to get shot at but take that hill by midnight" >> It's true. Well I mean, first of all, I think developers are in charge. I think one of the things that's happening is that it's clear is that every company, whether you're a start up or large enterprise, has to come to grips with if they're going to be a software company. And that's easy to say "Oh, that's easy. You just hire some software developers" No, it's not that easy. One, there's software developers coming out. But the way IT was built and the way people were buying IT, it's just not compatible with what software developers want to do. They want to work in a company that's actually building software. They don't want to be servicing infrastructure. So, saying that everyone's going to be a software company is one thing. That's true. And so that's the challenge. And I think Google has an opportunity. Just like Oedipus has been dominating with service-oriented approach managing services. By creating building blocks that create large Scale that allow people to write software easily. And I think that's the keyword. How do I make things common interface. You asked Diane Greene about common primitives. They're going to do the foundational work needed. It might be slower. But at a core primitive, they'll do that work. Because it'll make everything a faster. This is a different mind shift. So again, you also asked one of the guests, I forget who it was, IT moves at a very slow speeds. It's like a caravan-- >> You said glacial >> But yeah, well that used to be. But they have to move faster. So the challenge is: how do you blend the speed of technology, specifically on how modern software is being written, when you have Cloud Scale opportunities? Because this is not a cost cutting environment. People want to press the gas, not the brake. So you have a flywheel developing in technology, where if you are right on a business model observation, where you can create differentiation for a business, this is now the Cloud's customers. You know, you're a bank, you're a financial institution, you're manufacturing, you're a media company. If you can see an opportunity to create a competitive advantage, the Cloud is going to get you there really fast. So, I'm not too hung up on who has the better serverless. I look at it like a car. I want to drive the car. I always want to make sure the engine doesn't fall out or tires don't break. But so you got to look at it, this is a whole 'nother world. If you're not in the Cloud, you're basically on horse and buggy. So yeah, you're not going to have to buy hay. You don't have to deal with horses and clean up all the horse crap on the street. I mean all of that goes away. So IT, buying IT, is like horse and buggy. Cloud is like the sports car. And the question is 'Do I need air-conditioning?' 'Do I need power windows?' This is a whole new view. And people just want to get the job done. So this is about business. Future work. Making money. >> So-- >> And technology is going to facilitate that. So I think the Cloud game is going to get different very fast. >> Well I want to pick up on a couple things you said. Software, every company's becoming a software company. Take Andreessen, said 'Software is eating the world' If software's eating the world, data is eating software. So you've got to become a data company, as well as, a software company. And data has to be at the core of your business in order to compete. And data is not at the core of most company's businesses. So how do they close that gap? >> Yeah >> You've talked about the innovation sandwich. Cloud, data, and AI are sort of the cocktail that's going to drive innovation in the future. So if data is not at the core of your company, how are you going to close that AI gap? Well the way you're going to close is you're going to buy AI from companies like Google and Amazon and others. So that's one point. >> Yeah, and if you don't have an innovation sandwich, if you don't have the data, it's a wish sandwich. You wish you had some meat. >> You wish you had it right (Laughing) Wish I had some meat. You know the other thing is, you mentioned Diane Greene in her keynotes said "We provide consistency "with a common core set of primitives" And I asked her about that because it's really different than what Amazon does. So Amazon, if you think about Amazon data pipeline, and we know because were customers. We use DynamoDB, we use S3, we use all these different services in the data pipeline. Well, each of those has a different API. And you got to learn that world. What Google's doing, they're just simplifying that with a common set of primitives. Now, Diane mentioned, she said there's a trade off. It takes us longer to get to market if-- >> Yeah, but the problem is, here's the problem. Multicloud is a real dynamic. So even though they have a common set of primitives, if you go to Azure or AWS you still have different primitives over there. So the world of Multicloud isn't as simple as saying 'moving workloads' yet. So although you're startin' to see good signs within Google to say 'Oh, that's on prim, that's in the Cloud' 'Okay that's hybrid' within Google. The question is when I don't have to hire an IT staff to manage my deployments on Azure or my deployments on AWS. That's a whole different world. You still got to learn skill sets on those other-- >> That's true >> On other Clouds >> But as your pipeline, as your data pipeline grows and gets more and more complex, you've got to have skill sets that grow. And that's fine. But then it's really hard to predict where I should put data sometimes and what. Until you get the bill at the end of the month and you go "Oh I should've put that in S3 instead of Aurora" Or whatever it is. And so Google is trying to simplify that and solve that problem. Just a different philosophy. Stu Miniman asked Andy Jassy about this, and his answer on theCUBE was 'Look we want to have fine grain control over those primitives in case the market changes. We can make the change and it doesn't affect all the other APIs we have' So that was the trade off that they made. Number one. Number two is that we can get to market faster. And Diane admitted it slows us down but it simplifies things. Different philosophy. Which comes back to differentiation. If you're going to win in the enterprise you have to believe. I get the sense that these guys believe. >> Well and I think there's a belief but as an architectural decision, Amazon and Google are completely different animals. If you look at Amazon and you look at some of the decisions they make. Their client base is significantly larger. They've been in business longer. The sets of services they have dwarf Google. Google is like on the bar chart Andy Jassy puts up, it's like here, and then everyone else is down here, and Google's down here. >> Yeah and the customer references, I mean, it's just off the charts >> So Google is doing, they're picking their spots to compete in. But they're doing it in a very smart engineering way. They can bring out the big guns. And this is what I would do. I love this strategy. You got hardened large scale technology that's been used internally and you're not trying to peddle that to customers. You're tweaking it and making it consumable. Bigtable, BigQuery, Spanner. This is tech. Kubernetes. This is Google essentially being smart. Consuming the tech is not necessarily shoving it down someone's throat. Amazon, on the other hand, has more of a composability side. And some people will use some services on Amazon and not others. I wouldn't judge that right now. It's too early to tell. But these are philosophy decisions. We'll see how the bet pans out. That's a little bit longer term. >> I want to ask you about the Cisco deal. It seems like a match made in heaven. And I want to talk specifically about some of the enterprise guys, particularly Dell, Cisco, and HPE. So you got Dell, with VMware, in bed with Amazon in a big way. We were just down at DC last month, we heard all about that. And we're going to hear more about it this fall at re:Invent. Cisco today does a deal with Google. Perfect match, right? Cisco needs a cloud, Google needs an enterprise partner. Boom. Where's that leave HP? HP's got no cloud. All right, and are they trying to align? I guess Azure, right? >> Google's ascension-- >> Is that where they go? They fall to Azure? >> Well that's what habit is. That's the relationship. The Wintel. >> Right >> But back up with HP for a second. The ascension of Google Cloud into the upper echelon of players will hurt a few people. One of them's obviously Oracle, right? And they've mentioned Oracle and the Cloud Spanner thing. So I think Oracle will be flat-footed by, if Google Cloud continues the ascension. HPE has to rethink, and they kind of look bad on this, because they should be partnering with Google Cloud because they have no Cloud themselves. And the same with Dell. If I'm Dell and HP, I got to get out of the ITOps decimation that's coming. Because IT operations and the manageability piece is going to absolutely be decimated in the next five years. If you're in the ITOps business or IT management, ITOM, ITIL, it's going to get crushed. It's going to get absolutely decimated. It's going to get vaporized. The value is going to be shifted to another part of the stack. And if you're not looking at that if your HPE, you could essentially get flat-footed and get crushed. So HP's got to be thinking differently. But what Google and Amazon have, in my opinion, and you could even stretch and say Alibaba if you want a gateway to China, is that what the Wintel relationship of Windows and Intel back in the 80s and 90s that created massive innovations So I see a similar dynamic going on now, where the Cloud players, we call them Cloud native, Amazon and Google for instance, are creating that new dynamic. I didn't mention Microsoft because I don't consider them yet in the formal position to be truly enabling the kind of value that Google and Amazon will value because-- >> Really? Why not? >> Because of the tech. Well and I think Amazon is more, I mean Microsoft is more of a compatibility mode (Talking over each Other) I run Microsoft. I've got a single server. I've got Office. Azure's got good enough, I'm not really looking for 10-X improvement. So I think a lot of Microsoft's success is just holding the line. And the growth and the stock has been a function of the operating model of Cloud. And we'll see what they do at their show. But I think Microsoft has got to up their game a bit. Now they're not mailing it in. They're doing a good job. But I just think that Google and Amazon are stronger Cloud native players straight up on paper, right? And if you look up their capability. So the HPEs and the Ecosystems have to figure out who's the new partner that's going to make the market. And rising tide will float all boats. So to me, if I am at HP I'm thinking to myself "Okay, I got to manage services. "I better get out in front of the next wave "or I'm driftwood" >> Well Oracle is an interesting case too. You mentioned Oracle. And somebody said to me today 'Oracle they're really hurting' And I'm like most companies would love to be hurting that badly but-- >> Oracles not hurting >> Their strategy of same-same but it's the same Oracle stack brought into the Cloud. They're sending a message to the customers 'Look you don't have to go to another Cloud. 'We've got you covered. We're investing in R&D', which they do by the way. But it was really interesting to hear from the Cloud Spanner customer today that they got a 10-X value, 10-X reduction in costs, and a 10-X capability of scaling relative to Oracle that was powerful to hear that. >> There's no doubt in my mind. Oracle's not hurting. Oracle's got thousands and thousands of customers that do hundreds of millions of dollars in revenue. And categories that people would love to have. The question on Oracle is the price pressure is an innovator's dilemma because there's no doubt that Oracle could just snap a few fingers and replicate the kind of deliverables that people are offering. The question is can they get the premium that they're used to getting. One. Number two, if everyone's a software company, are they truly delivering the value that's expected. To be a software company, to be competitive, not to make the lights run-- >> To enable >> To enable competitive-- (Talking over each other) Competitive advantage at a level, that's to me, going to be the real test of how Cloud morphs. And I question that you got to be agile and have a real top line revenue numbers where using technology at a cost benefit ratio that drives value-- >> But with Oracle-- >> If Oracle can get there then that's what we'll see >> The reason why they'll continue to win is because they move at the speed of the CIO. The CIO, and they'll say all the right things: AI-infused, block chain, and machine learning, and all that stuff. And the CIOs will eat it up because it's a safe bet. >> Well, I want to get your thoughts because I talked about this a couple years ago. Last year we started harping on it. We got it more into theCUBE conversation around Cloud being horizontally scalable yet at the top of the stack you've got vertical differentiation. That's great for data. Diane Greene in her key notes said that the vertical focus with engineering resources tied to it it's a key part of their strategy. Highlighted healthcare was their first vertical. Talked about National Institute of Health deal-- >> Retail >> NGOs, financial service, manufacturing, transportation, gaming and media. You got Fortnight on there, a customer in both Clouds. Start ups and retail. >> Yeah he had the target cities >> Vertical strategy is kind of an old enterprise play book TABE. Is that a viable one? Because now with the kind of data, if you got the data sandwich, maybe specialism and verticals can Scale. Your thoughts? >> I'll tell you why it is. I'll tell you why it's viable. Because of digital. So for years, these vertical stacks have been hardened. And the expertise and the business process and the knowledge within that vertical industry, retail, transportation, financial services, etc., has been hardened. But with digital, you're seeing it all over the place. Amazon getting into content. Apple getting into content. Amazon getting into groceries. Google getting into healthcare. So digital allows you to not only disrupt horizontally at the technology layer, but also vertically within industries. I think it's a very powerful disruption agenda. >> Analytics seems to be the killer app. That's the theme here: data. Maybe take it to the next step. That's where the specialism is. That's where the value's created. Why not have vertical specialty? >> No and >> Makes a lot of sense >> And it's a different spin. It's not the traditional-- >> Stack >> Sort of hire a bunch of people with that knowledge in that stack. No, it's really innovate and change the game and change the business model. I love it. >> That was a great surprise to me. Dave, great kicking off day one here this morning. Ending day one here with this wrap up. We got three days of wall-to-wall coverage. Go to siliconANGLE.com. We've got a great Cloud special Rob Hof, veteran chief of the team. Mark Albertson, and the rest of the crew, put some great stories together. Go to theCUBE.net and check out the video coverage there. That's where we're going to be live. And of course WIKIBAN.com for the analyst coverage from Peter Burris and his team. Check that out. Of course theCUBE here. Day one. Thanks for watching. See you tomorrow

(music) >> From San Francisco, it's theCUBE. Covering Girls in Tech Catalyst Conference brought to you by Girls in Tech. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco at the Girls in Tech Catalyst event. Really great event, about 700 people, couple days. It's just a single track, a lot of presentations, about 20-minute presentations, by a bunch of female leaders telling their story, how did they get where they got. What advice could they give. And there's men, women here. They just brought in, I think, a busload of students. So it's a really great event. We're excited to be here and we're psyched for our next guest. She's Rashmi Kumar, the SVP Supply Chain and Procurement from McKesson, welcome. >> Hi, thank you Jeff. >> Absolutely, so you said you hadn't been to this event before. You keep trying to come, but things don't, keep getting in the way. So, what do you think, now that you're here? >> Absolutely, I'm so glad to be here. I'm so thankful to McKesson for being the lead sponsor of the event. I'm really excited to see the energy here. >> Yeah, so how did McKesson become the lead sponsor cause that's a really nice statement on the company to really get involved in something like Girls in Tech. >> Yeah, so McKesson is a company which is sitting at the intersection of healthcare. Guess what, it's something on which our lives depend on. But this is the industry which is most behind in technology. So we want to do everything to grow technology talent across the country in this space to enable better health care for our patients. >> Right. It's interesting, we talked before we turned the cameras on that there's still a huge talent gap. It's funny cause we go to a lot of shows and they talk about the machines are taking all the jobs and there's not going to be jobs for people. But, in fact, there's still a ton of jobs, there's still a ton of opportunity in tech. We still don't have enough people so we have to bring in women, we have to bring in other folks to help fill all these great opportunities. >> Yeah, absolutely. When we talk about machine and AI, we are not talking about pure AI taking away the job. It will be enabling human being to do better job and will improve our quality of life. Who will build those machines, though? You need technologists, we need technologists who will build that machine and we are here to grow ourselves and grow our people. Sitting where I am at SVP of Supply Chain role, all the commerce is moving from store front to e-commerce. That is run by programs and technologies and there are jobs in warehouses for people to enable the e-commerce but how do we build those platforms that will enable our patients to get their medication at their doorsteps and not have to go run from pharmacy to pharmacy to find it. We need technologists for it. >> It's interesting because supply chain's been automized for a long time and early days of tech innovation where is was ERP and SAP. So what lessons can you tell from procurement that now we see in more customer-facing and direct-to-consumer tech involvement? Because you still have people, you still there's a lot of automation in procurement, but you still have a lot of things for people to do. >> Yeah, so as the supply chain was more business-to-business we were focused on the customer experience of for, say, pharmacists or the experience of a person who was working on the warehouse floor. And we didn't worry about it, the gray screens, green screens, whatever we put. Now you think about an autonomous car or you think about a drone delivering medicine... You need to give the interaction to every person which enables them to consume those services. This whole field of human computer interaction is new. >> [Jeff} Yeah. >> Machines will run the cars and we don't have to drive it. How I interact with it, somebody needs to define it and then tweak it and grow it. That's also another point about all technology and digital product. You can pivot and change and bring in new functionality, satisfy human consumerization of technologies, changing human needs to interact with technology as well. And we need all kinds of people, from all backgrounds because diversity brings in diverse thinking, which brings in better products. >> Yeah, it does. It's not only the right thing to do, but it actually delivers much better results and bottom line. So you're here, you're running a workshop today. So tell us a little bit about the workshop that you're running. >> Yeah, so the workshop, my topic is make your pitch perfect, which is around the whole topic of elevator pitch. But because it's Girls in Tech Conference, we women want to be 200% sure that we are good to do a job and we don't branch out to highlight the work that we are doing already. Which could get us in that next position. So, how as a professional we should interact with not only our managers and peers, but other leaders within the company. Maybe other leaders across my industry as well as in technology and impress them with what I can do so that we leave a lasting impression on the peson's mind and when he or she is looking for a role, for a person for a role, they think of the girls who are here >> Right. >> Training these two days. This is just kind of the icing on the cake. >> So what are some of the tips and tricks for the people that didn't make the conference that you help them with? Are there some common errors that people make over and over and over that you're trying to tell them not to do? Are there a couple little guideposts that you can help them to get their pitch down? Is it the timing? Is it the focus? Is it the way it's structured? What are some of the things you share with them? >> Absolutely. So HBR did an article on elevator pitch for elevator pitch. (Jeff laughing) >> I've got to see that one. >> That means that that we leave lot of interactions on the table because when we are riding in elevator, riding in train or just sitting at a bar we don't take the opportunity to open up that conversation so we'll be focusing on that a little bit. And then also talking about, as you define your individual pitch think about your own passion, your own skill and where does it fit with some companies' or some projects' need? At that intersection lies the sweet spot for that person and how they hone and how they really practice it and have it handy and available to say it when the time comes, right? So that's the main kind of gist of the workshop. >> Well, and it's an interesting concept, too, because we go to a lot of conferences and one of the great values of conferences if you're exhibiting is you get to practice your pitch with a whole bunch of people over a really short period of time and hone it so it's an interesting concept to take advantage of those opportunities maybe if they're not even great ones but just to get the reps in, just to see what resonates, what do people listen to, what do they grab? >> Right, so they will do a practice. >> Right, right. >> Think about what their skill, what they're passion about, what does the place where they want to go need and see the intersection. And maybe the places they're thinking of might not fit their passion and skill but they're just enamored with that place so it also kind of gives them some toolbox to think ahead of time around how to plan their careers. >> All right, well, important work and again, thank you for your sponsorship of the conference. It's really important and it's a great, great statement on McKesson. >> Thank you. >> All right. She's Rashmi. I'm Jeff. We are at Girls in Tech Catalyst 2018, downtown San Francisco. Thanks for watching. >> Thank you. (music)

(music) >> From San Francisco, it's theCUBE. Covering Girls in Tech Catalyst Conference brought to you by Girls in Tech. >> Hey, welcome back everybody. Jeff Frick here with theCUBE. We're in downtown San Francisco at the Girls in Tech Catalyst event. Really great event, about 700 people, couple days. It's just a single track, a lot of presentations, about 20-minute presentations, by a bunch of female leaders telling their story, how did they get where they got. What advice could they give. And there's men, women here. They just brought in, I think, a busload of students. So it's a really great event. We're excited to be here and we're psyched for our next guest. She's Rashmi Kumar, the SVP Supply Chain and Procurement from McKesson, welcome. >> Hi, thank you Jeff. >> Absolutely, so you said you hadn't been to this event before. You keep trying to come, but things don't, keep getting in the way. So, what do you think, now that you're here? >> Absolutely, I'm so glad to be here. I'm so thankful to McKesson for being the lead sponsor of the event. I'm really excited to see the energy here. >> Yeah, so how did McKesson become the lead sponsor cause that's a really nice statement on the company to really get involved in something like Girls in Tech. >> Yeah, so McKesson is a company which is sitting at the intersection of healthcare. Guess what, it's something on which our lives depend on. But this is the industry which is most behind in technology. So we want to do everything to grow technology talent across the country in this space to enable better health care for our patients. >> Right. It's interesting, we talked before we turned the cameras on that there's still a huge talent gap. It's funny cause we go to a lot of shows and they talk about the machines are taking all the jobs and there's not going to be jobs for people. But, in fact, there's still a ton of jobs, there's still a ton of opportunity in tech. We still don't have enough people so we have to bring in women, we have to bring in other folks to help fill all these great opportunities. >> Yeah, absolutely. When we talk about machine and AI, we are not talking about pure AI taking away the job. It will be enabling human being to do better job and will improve our quality of life. Who will build those machines, though? You need technologists, we need technologists who will build that machine and we are here to grow ourselves and grow our people. Sitting where I am at SVP of Supply Chain role, all the commerce is moving from store front to e-commerce. That is run by programs and technologies and there are jobs in warehouses for people to enable the e-commerce but how do we build those platforms that will enable our patients to get their medication at their doorsteps and not have to go run from pharmacy to pharmacy to find it. We need technologists for it. >> It's interesting because supply chain's been automized for a long time and early days of tech innovation where is was ERP and SAP. So what lessons can you tell from procurement that now we see in more customer-facing and direct-to-consumer tech involvement? Because you still have people, you still there's a lot of automation in procurement, but you still have a lot of things for people to do. >> Yeah, so as the supply chain was more business-to-business we were focused on the customer experience of for, say, pharmacists or the experience of a person who was working on the warehouse floor. And we didn't worry about it, the gray screens, green screens, whatever we put. Now you think about an autonomous car or you think about a drone delivering medicine... You need to give the interaction to every person which enables them to consume those services. This whole field of human computer interaction is new. >> [Jeff} Yeah. >> Machines will run the cars and we don't have to drive it. How I interact with it, somebody needs to define it and then tweak it and grow it. That's also another point about all technology and digital product. You can pivot and change and bring in new functionality, satisfy human consumerization of technologies, changing human needs to interact with technology as well. And we need all kinds of people, from all backgrounds because diversity brings in diverse thinking, which brings in better products. >> Yeah, it does. It's not only the right thing to do, but it actually delivers much better results and bottom line. So you're here, you're running a workshop today. So tell us a little bit about the workshop that you're running. >> Yeah, so the workshop, my topic is make your pitch perfect, which is around the whole topic of elevator pitch. But because it's Girls in Tech Conference, we women want to be 200% sure that we are good to do a job and we don't branch out to highlight the work that we are doing already. Which could get us in that next position. So, how as a professional we should interact with not only our managers and peers, but other leaders within the company. Maybe other leaders across my industry as well as in technology and impress them with what I can do so that we leave a lasting impression on the peson's mind and when he or she is looking for a role, for a person for a role, they think of the girls who are here >> Right. >> Training these two days. This is just kind of the icing on the cake. >> So what are some of the tips and tricks for the people that didn't make the conference that you help them with? Are there some common errors that people make over and over and over that you're trying to tell them not to do? Are there a couple little guideposts that you can help them to get their pitch down? Is it the timing? Is it the focus? Is it the way it's structured? What are some of the things you share with them? >> Absolutely. So HBR did an article on elevator pitch for elevator pitch. (Jeff laughing) >> I've got to see that one. >> That means that that we leave lot of interactions on the table because when we are riding in elevator, riding in train or just sitting at a bar we don't take the opportunity to open up that conversation so we'll be focusing on that a little bit. And then also talking about, as you define your individual pitch think about your own passion, your own skill and where does it fit with some companies' or some projects' need? At that intersection lies the sweet spot for that person and how they hone and how they really practice it and have it handy and available to say it when the time comes, right? So that's the main kind of gist of the workshop. >> Well, and it's an interesting concept, too, because we go to a lot of conferences and one of the great values of conferences if you're exhibiting is you get to practice your pitch with a whole bunch of people over a really short period of time and hone it so it's an interesting concept to take advantage of those opportunities maybe if they're not even great ones but just to get the reps in, just to see what resonates, what do people listen to, what do they grab? >> Right, so they will do a practice. >> Right, right. >> Think about what their skill, what they're passion about, what does the place where they want to go need and see the intersection. And maybe the places they're thinking of might not fit their passion and skill but they're just enamored with that place so it also kind of gives them some toolbox to think ahead of time around how to plan their careers. >> All right, well, important work and again, thank you for your sponsorship of the conference. It's really important and it's a great, great statement on McKesson. >> Thank you. >> All right. She's Rashmi. I'm Jeff. We are at Girls in Tech Catalyst 2018, downtown San Francisco. Thanks for watching. >> Thank you. (music)

>> Announcer: From the Corinium Chief Analytics Officer Conference Spring, San Francisco It's theCUBE. >> Hey welcome back, everybody, Jeff Frick here with theCUBE. We're in downtown San Francisco at the Corinium Chief Analytics Officer Spring Event about a hundred CAO's as opposed to CDO's talking about big data, transformation and analytics and the role of analytics and a lot of practitioners are really excited to have our next guest. He's up from Mexico City, it's Jose Murillo. He's the chief analytics officer from Banorte. Jose, great to see you. >> Thank you for having me, Jeff. >> Absolutely, so for people that aren't familiar with Banorte give us a quick overview. >> Banorte's the second largest financial group in Mexico. We, for the last, during the last three years were able to leapfrog city bank. >> Congratulations, and as we were talking before we turned the cameras on, you and your project had a big part of that. So before we get in it, you are a chief analytics officer. How did you come in, what's the reporting structure, how do you work within the broader spectrum of the bank? >> Well I moved to Banorte like about five years ago from, I was working at the central bank where I spent about 10 years in the MPC, the Monitor Policy Committee, and I was invited by initially by the president of the board and when the new chief operating officer was named he invited me to, to lead a new analytics business unit that he wanted to create. And that's the way that I arrived there. >> Okay so you report in to the COO. >> He's the COO/CFO, so he's not only a very smart guy but a very powerful guy running the organization. >> And does the CIO also report to him? >> The CIO, the CDO, the CMO report to him. >> Okay so you have a CDO as well Chief Data Officer. >> We have a CDO who I work very close with him. >> We could go for a long time I might not let you leave for lunch. So I'm just curious on the relationship between the CDO and the CAO, the data officer and the analytics officer. We often hear one or the other, it's very seldom that I've heard both. So how do you guys divide and conquer your responsibilities? How do you parse that out? >> I guess he provides the foundation that we need to find analytics projects that are going to transform the financial group and he has been a very good partner in providing the data that we need and basically what we do as the CAO we find those opportunities to improve the efficiency, to bring the customer to the center, and be able to deliver value to our stakeholders. >> Right, so he's really kind of giving you the infrastructure if you will, of making that data available, getting it to you from all various sources, et cetera, that then you can use for your analytics magic on top. >> Exactly >> Okay, so that's very good, so when we sat down you said an exciting report has come out from, I believe it was HBR, about the tremendous ROI that you guys have realized. So you tell the story better than I, what did they find in your recent article? >> Well in the recent article from the Harvard Business Review is how Banorte has made its analytics business unit pay off. And what we have found in the past two and a half years is we've been able to deliver massive value and by now we have surpassed a billion dollars in net income creation. From analytics projects made on cost saving strategies and revenue generating projects. >> So you paid for yourself just barely >> Yeah. >> No I mean that's such a great story, just barely 'cause it's so it's so important. So as you said, that billion dollars have been realized both in cost savings but more importantly on incremental revenue and that's really the most important thing. >> Exactly >> So how are you measuring that ROI? >> So basically the way we measure it is on cost saving strategies that are related to a risk operational and financial cost. It's the contemporary news effect. And that can be audited. And on the other side, on revenue generating projects, the way we do it is we estimate the customer lifetime value, which is nothing else than the net present value of the relationship with our customers, so we need to estimate survival rates plus the depth of the relationship with our customers. >> So I just love, so you're doing all kinds of projects, you're measuring the value of the projects. What are some of the projects that had a high ROI that you would've never guessed that you guys applied some analytics to and said wow, terrific value relative to what we expected. >> Let me tell you about two types of projects. The first project that we started on was on cost of risk cutting strategies. And we delivered massive value and very quickly. So that helped us gain credibility. And the way we do it, we did it, is like to analyze a dicing of the data where we had excessive cost of risk. And in the first year, actually, that was the first quarter of Operations, we yielded about a 25% incremental value to the credit card business. And after that, we start to work with them and started the discovery data process. And from there, we were able to optimize analytically the cross cell process. And that's a project that has already a three year maturity. And by this time, we are able to sell, without having any bricks or mortars, about 25% of the credit cards sold by the financial group. If we were a territory within the financial group, we would be the largest one with 400 basis points lower on cost of risk, 30% more on activation rates. And it's no surprise that the acquisition cost is 30% less, vis-a-vis our most efficient channel. >> Right, I just want to keep digging down into this, Jose, there's a lot of this stuff to go. I mean, you've been issuing cards forever. So was it just a better way to score customers, was it a better way to avoid the big fraud customers, was it a better way to steal customers maybe from a competitor with a competitive rate that you can afford, I mean, what are some of the factors that allowed you to grow this business in such a big way? >> I guess it's something that has been improving during the first three years. The first thing is that we made like, a very simple cascade on seeing why we were not that efficient cross cell process. And we kind of fixed every part of it. Like on the income estimation models that we had, and we partner with the risk department to improve them. Up to the information that we had on our customers to contact them, and we partner with data governance to improve those. And finally, on the delivery process and all the engaging process with the customers. And it seemed that we were going to find something that was going to be more costly, but it was something that we had at the center of the customers so that it was more likely for them to go and pick up the card and we deliver it to their homes. And finally, that process was much more efficient and the gains that we had, we shared them with our customers. And after three years, we've done things with artificial intelligence to have much better scripts so that we are better able to serve our customers. We do a lot of experimentation, experimentation that we didn't do before. And we use some concepts from behavioral economics to try to explain much better the value proposition to our customers. >> So I just, I love this point, is that it was a bunch of small, it was optimizing lots of little steps and little pieces of the pie that added up to such a significant thing, it wasn't like this magic AI pixie dust. >> Initially, it as a big bang, and then it has been something incremental that has since, it's a project that at the end of the day, we own, and it's something that we are tracking. We are willing to put all the effort to have all the incremental efficiency within the process. >> So people, process, and technology, we talk about, those are the three pieces always to drive organizational change. And usually, the technology is the easy part, the hard part is the people and the process. So as you and your team have started to work with the various lines of businesses for all these different pieces. Promotional piece, customary attention piece, risk and governance piece, cross sale pice, how has their attitude towards your group changed over time as you've started to deliver insight and all this incremental deltas into their business. >> I guess you are hitting just on the spot. Building the models is the easy part. The hard part is to build the consensus around, to change a process that has run for 20 years, there's a lot of inertia. >> Right, right. >> And there are a lot of silos within organizations. So initially, I guess, the credibility that we gained initially helped us move faster. And at the end of the day, I think what happens is the way that we are set up is that the incentives are very well aligned within the different units that need to interact in the sense that we are a unit that is sponsored by the, corporately sponsored, and we make it easier for our partners to attain their goals. So that's, and they don't share the cost of us, so that helps. >> And those are the goals they already had. So you're basically helping them achieve their objectives that they already had better and more efficiently. >> Yeah, and you are pointing out correctly, it's the people, and besides the math, it's a highly, you could say diplomatic or political position in the sense that you need to have all the different partners and stakeholders aligned to change something that has been running for 20 years. >> Right, right. And i just love it, it's a ton of little marginal improvements across a wide variety of tough points, it's so impactful. So as you look forward now, is there another big bang out there, or do you just see kind of this constant march of incremental improvement, and, or are you just going to start getting into more different businesses or kind of different areas in the bank to apply the same process, where do you go next? >> Well, we started with the credit card business, but we moved toward the verticals within the financial group. From mortgages, auto loans, payroll loans, to we are working with the insurance company, the long term savings company. So we've increased the scope of the group. And we moved not only from cost to revenue generating projects. And so far, it has been, we have been on an exponential increase of our impact, I guess that's the big question. The first, we were able to do 46 times our cost. The second year, we made 106 times our cost, the third year, we are close to 200 times our cost with an incremental base. And so far, we've been on this increasing slide. At some point, it's, I guess, we are going to decelerate, but so far, we haven't hit the point. >> Right, the law of big numbers, eventually, you got to, eventually, you'll slow down a little bit. All right, well Jose, I'll give you the last word before we sign off here. Kind of tips and tricks that you would share with a peer if we're sitting around on a Friday afternoon on a back porch. You know, as you've gone through this journey, three and a half years and really sold you and your vision into the company, what would you share with a peer that's kind of starting this journey or starting to run into some of the early hurdles to get past. >> I guess there are two things that I could share. And once you have built a group like this and you have already, the incentives aligned and you have support from the top in the sense that they know that there's no other way they want really to compete and be successful, and suppose that you have all these preconditions set up and suddenly, you have a bunch of really smart people that are coming to a company, so you need to focus on ROI, high ROI projects. I;s very easy to get distracted on non-impactful projects. And I guess, the most important thing is that you have to learn to say no to a lot of things. >> Speaking my language, I love it. Learn to say no, it's the most important thing you'll ever, all right, well Jose, thanks for spending a few minutes and congratulations on all your success, what a great story. >> Thank you for having me, Jeff. >> Absolutely, he's Jose, I'm Jeff, you're watching theCUBE from the Corinium Chief Analytics Officer Summit in downtown San Francisco. (electronic music)

>> Live from Boston, Massachusetts, it's The Cube! Covering IBM Chief Data Officer Summit, brought to you by IBM. >> Welcome back to The Cube's live coverage of IBM's Chief Data Strategy Summit, I'm your host Rebecca Knight, along with my cohost Dave Vellante. We have a big panel today, these are our social influencers. Starting at the top, we have Christopher Penn, VP Marketing of Shift Communications, then Tripp Braden, Executive Coach and Growth Strategist at Strategic Performance Partners, Mike Tamir, Chief Data Science Officer at TACT, Bob Hayes, President of Business Over Broadway. Thanks so much for joining us. >> Thank you. >> So we're talking about data as a way to engage customers, a way to engage employees. What business functions would you say stand to benefit the most from using data? >> I'll take a whack at that. I don't know if it's the biggest function, but I think the customer experience and customer success. How do you use data to help predict what customers will do, and how do you then use that information to kind of personalize that experience for them and drive up recommendations, retention, upselling, things like that. >> So it's really the customer experience that you're focusing on? >> Yes, and I just released a study. I found that analytical-leading companies tend to use analytics to understand their customers more than say analytical laggards. So those kind of companies who can actually get value from data, they focus their efforts around improving customer loyalty by just gaining a deeper understanding about their customers. >> Chris, you want to jump in here with- >> I was just going to say, as many of us said, we have three things we really care about as business people, right? We want to save money, save time, or make money. So any function that meets those qualifications, is a functional benefit from data. >> I think there's also another interesting dimension to this, when you start to look at the leadership team in the company, now having the ability to anticipate the future. I mean now, we are no longer just looking at static data. We are now looking at anticipatory capability and seeing around corners, so that the person comes to the team, they're bringing something completely different than the team has had in the past. This whole competency of being able to anticipate the future and then take from that, where you take your organization in the future. >> So follow up on that, Tripp, does data now finally trump gut feel? Remember the HBR article of 10, 15 years ago, can't beat gut feel? Is that, we hit a new era now? >> Well, I think we're moving into an era where we have both. I think it's no longer an either or, we have intuition or we have data. Now we have both. The organizations who can leverage both at the same time and develop that capability and earn the trust of the other members by doing that. I see the Chief Data Officer really being a catalyst for organizational change. >> So Dr. Tamir I wonder if I could ask you a question? Maybe the whole panel, but so we've all followed the big data trend and the meme, AI, deep learning, machine learning, same wine, new bottle, or is there something substantive behind it? >> So certainly our capabilities are growing, our capabilities in machine learning, and I think that's part of why now there's this new branding of AI. AI is not what your mother might have thought AI is. It's not robots and cylons and that sort of thing that are going to be able to think intelligently. They just did intelligence tests on the different, like Siri and Alexa, quote AIs from different companies, and they scored horribly. They scored much worse than my, much worse than my very intelligent seven-year old. And that's not a comment on the deficiencies in Alexa or in Siri. It's a comment on these are not actually artificial intelligences. These are just tools that apply machine learning strategically. >> So you are all thinking about data and how it is going to change the future and one of the things you said, Tripp, is that we can now see the future. Talk to me about some of the most exciting things that you're seeing that companies do that are anticipating what customers want. >> Okay, so for example, in the customer success space, a lot of Sass businesses have a monthly subscription, so they're very worried about customer churn. So companies are now leveraging all the user behavior to understand which customers are likely to leave next month, and if they know that, they can reach out to them with maybe some retention campaigns, or even use that data to find out who's most likely to buy more from you in the next month, and then market to those in effective ways. So don't just do a blast for everybody, focus on particular customers, their needs, and try to service them or market to them in a way that resonates with them that increases retention, upselling, and recommendations. >> So they've already seen certain behaviors that show a customer is maybe not going to re-up? >> Exactly, so you just, you throw this data in a machine learning, right. You find the predictors of your outcome that interest you, and then using that information, you say oh, maybe predictors A, B, and C, are the ones that actually drive loyalty behaviors, then you can use that information to segment your customers and market to them appropriately. It's pretty cool stuff. >> February 18th, 2018. >> Okay. >> So we did a study recently just for fun of when people search for the term "Outlook, out of office." Yeah, and you really only search for that term for one reason, you're going on vacation, and you want to figure out how to turn the feature on. So we did a five-year data poll of people, of the search times for that and then inverted it, so when do people search least for that term. That's when they're in the office, and it's the week of February 18th, 2018, will be that time when people like, yep, I'm at the office, I got to work. And knowing that, prediction and data give us specificity, like yeah, we know the first quarter is busy, we know between memorial Day and Labor Day is not as busy in the B to B world. But as a marketer, we need to put specificity, data and predictive analytics gives us specificity. We know what week to send our email campaigns, what week to turn our ad budgets all the way to full, and so on and so forth. If someone's looking for The Cube, when will they be doing that, you know, going forward? That's the power of this stuff, is that specificity. >> They know what we're going to search for before we search for it. (laughter) >> I'd like to know where I'm going to be next week. Why that date? >> That's the date that people least search for the term, "Outlook, out of office." >> Okay. >> So, they're not looking for that feature, which logically means they're in the office. >> Or they're on vacation. (laughter) Right, I'm just saying. >> That brings up a good point on not just, what you're predicting for interactions right now, but also anticipating the trends. So Bob brought up a good point about figuring out when people are churning. There's a flip side to that, which is how do you get your customers to be more engaged? And now we have really an explosion in reinforcement learning in particular, which is a tool for figuring out, not just how to interact with you right now as a one off, statically. But how do I interact with you over time, this week, next week, the week after that? And using reinforcement learning, you can actually do that. This is the the sort-of technique that they used to beat Alpha-Go or to beat humans with Alpha-Go. Machine-learning algorithms, supervised learning, works well when you get that immediate feedback, but if you're playing a game, you don't get that feedback that you're going to win 300 turns from now, right now. You have to create more advanced value functions and ways of anticipating where things are going, this move, so that you see things are on track for winning in 20, 30, 40 moves, down the road. And it's the same thing when you're dealing with customer engagement. You want to, you can make a decision, I'm going to give this customer a coupon that's going to make them spend 50 cents more today, or you can make decisions algorithmically that are going to give them a 50 cent discount this week, next week, and the week after that, that are going to make them become a coffee drinker for life, or customer for life. >> It's about finding those customers for life. >> IBM uses the term cognitive business. We go to these conferences, everybody talks about digital transformation. At the end of the day it's all about how you use data. So my question is, if you think about the bell curve of organizations that you work with, how do they, what's the shape of that curve, part one. And then part two is, where do you see IBM on that curve? >> Well I think a lot of my clients make a living predicting the future, they're insurance companies and financial services. That's where the CDO currently resides and they get a lot of benefit. But one of things we're all talking about, but talking around, is that human element. So now, how do we take the human element and incorporate this into the structure of how we make our decisions? And how do we take this information, and how do we learn to trust that? The one thing I hear from most of the executives I talk to, when they talk about how data is being used in their organizations is the lack of trust. Now, when you have that, and you start to look at the trends that we're dealing with, and we call them data points verses calling them people, now you have a problem, because people become very, almost analytically challenged, right? So how do we get people to start saying, okay, let's look at this from the point of view of, it's not an either or solution in the world we live in today. Cognitive organizations are not going to happen tomorrow morning, even the most progressive organizations are probably five years away from really deploying them completely. But the organizations who take a little bit of an edge, so five, ten percent edge out of there, they now have a really, a different advantage in their markets. And that's what we're talking about, hyper-critical thinking skills. I mean, when you start to say, how do I think like Warren Buffet, how do I start to look and make these kinds of decisions analytically? How do I recreate an artificial intelligence when machine-learning practice, and program that's going to provide that solution for people. And that's where I think organizations that are forward-leaning now are looking and saying, how do I get my people to use these capabilities and ultimately trust the data that they're told. >> So I forget who said it, but it was early on in the big data movement, somebody said that we're further away from a single version of the truth than ever, and it's just going to get worse. So as a data scientist, what say you? >> I'm not familiar with the truth quote, but I think it's very relevant, well very relevant to where we are today. There's almost an arms race of, you hear all the time about automating, putting out fake news, putting out misinformation, and how that can be done using all the technology that we have at our disposal for disbursing that information. The only way that that's going to get solved is also with algorithmic solutions with creating algorithms that are going to be able to detect, is this news, is this something that is trying to attack my emotions and convince me just based on fear, or is this an article that's trying to present actual facts to me and you can do that with machine-learning algorithms. Now we have the technology to do that, algorithmically. >> Better algos than like and share. >> From a technological perspective, to your question about where IBM is, IBM has a ton of stuff that I call AI as a service, essentially where if you're a developer on Bluemix, for example, you can plug in to the different components of Watson at literally pennies per usage, to say I want to do sentiment analysis, I want to do tone analysis, I want personality insights, about this piece, who wrote this piece of content. And to Dr. Tamir's point, this is stuff that, we need these tools to do things like, fingerprint this piece of text. Did the supposed author actually write this? You can tell that, so of all the four magi, we call it, the Microsoft, Amazon, Google, IBM, getting on board, and adding that five or ten percent edge that Tripp was talking about, is easiest with IBM Bluemix. >> Great. >> Well, one of the other parts of this is you start to talk about what we're doing and you start to look at the players that are doing this. They are all organizations that I would not call classical technology organizations. They were 10 years ago, look at a Microsoft. But you look at the leadership of Microsoft today, and they're much more about figuring out what the formula is for success for business, and that's the other place I think we're seeing a transformation occurring, and the early adopters, is they have gone through the first generation, and the pain, you know, of having to have these kinds of things, and now they're moving to that second generation, where they're looking for the gain. And they're looking for people who can bring them capability and have the conversation, and discuss them in ways that they can see the landscape. I mean part of this is if you get caught in the bits and bites, you miss the landscape that you should be seeing in the market, and that's why I think there's a tremendous opportunity for us to really look at multiple markets of the same data. I mean, imagine looking and here's what I see, everyone in this group would have a different opinion in what they're seeing, but now we have the ability to see it five different ways and share that with our executive team and what we're seeing, so we can make better decisions. >> I wonder if we could have a frank conversation, an honest conversation about the data and the data ownership. You heard IBM this morning, saying hey we're going to protect your data, but I'd love you guys, as independents to weigh in. You got this data, you guys are involved with your clients, building models, the data trains the model. I got to believe that that model gets used at a lot of different places, within an industry, like insurance or across retail, whatever it is. So I'm afraid that my data is, my IP is going to seep across the industry. Should I not be worried about that? I wonder if you guys could weigh in. >> Well if you work with a particular vendor, sometimes vendors have a stipulation that we will not share your models with other clients, so you just got to stick to that. But in terms of science, I mean you build a model, right? You want to generalize that to other businesses. >> Right! >> (drowned out by others talking) So maybe if you could work somehow with your existing clients, say here, this is what we want to do, we just want to elevate the waters for everybody, right? So everybody wins when all boats rise, right? So if you can kind of convince your clients that we just want to help the world be better, and function better, make employees happier, customers happier, let's take that approach and just use models in a, that may be generalized to other situations and use them. If if you don't, then you just don't. >> Right, that's your choice. >> It's a choice, it's a choice you have to make. >> As long as you're transparent about it. >> I'm not super worried, I mean, you, Dave, Tripp, and I are all dressed similarly, right? We have the model of shirt and tie so, if I put on your clothes, we wouldn't, but if I were to put on your clothes, it would not be, even though it's the same model, it's just not going to be the same outcome. It's going to look really bad, right, so. Yes, companies can share the models and the general flows and stuff, but there's so much, if a company's doing machine learning well, there's so much feature engineering that's unique to that company that trying to apply that somewhere else, is just going to blow up. >> Yeah, but we could switch ties, like Tripp has got a really cool tie, I'd be using that tie on July 4th. >> This is turning into a different kind of panel (laughter) Chris, Tripp, Mike, and Bob, thanks so much for joining us. This has been a really fun and interesting panel. >> Thank you very much. Thank you. >> Thanks you guys. >> We will have more from the IBM Summit in Boston just after this. (techno music)

>> Announcer: Live from Munich, Germany; it's The Cube! Covering IBM Fast Track Your Data, brought to you by IBM. >> Welcome back to Munich, Germany everybody. This is The Cube, the leader in live tech coverage. We're covering Fast Track Your Data, IBM's signature moment here in Munich. Big themes around GDPR, data science, data science being a team sport. I'm Dave Vellante, I'm here with my co-host Jim Kobielus. Marc Altshuller is here, he's the general manager of IBM Business Analytics. Good to see you again Marc. >> Hey, always great to see you. Welcome, it's our first time together. >> Okay so we heard your key note, you were talking about the caveats of correlations, you were talking about rear view mirror analysis versus sort of looking forward, something that I've been sort of harping on for years. You know, I mean I remember the early days of "decision support" and the promises of 360 degree views of the customer, and predictive analytics, and I've always said it, "DSS really never lived up to that", y'know? "Will big data live up to that?" and we're kind of living that now, but what's your take on where we're at in this whole databean? >> I mean look, different customers are at different ends of the spectrum, but people are really getting value. They're becoming these data driven businesses. I like what Rob Thomas talked about on stage, right. Visiting companies a few years ago where they'd say "I'm not a technology company.". Now, how can you possibly say you're not a technology company, regardless of the industry. Your competitors will beat you if they are using data and you're not. >> Yeah, and everybody talks about digital transformation. And you hear that a lot at conferences, you guys haven't been pounding that theme, other than, y'know below the surface. And to us, digital means data, right? And if you're going to transform digitally, then it's all about the data, you mentioned data driven. What are you seeing, I mean most organizations in our view aren't "data driven" they're sort of reactive. Their CEO's maybe want to be data driven, maybe they're aboard conversations as to how to get there, but they're mostly focused on "Alright, how do we keep "the lights on, how do we meet our revenue targets, "how do we grow a little bit, and then whatever money "we have leftover we'll try to, y'know transform." What are you seeing? Is that changing? >> I would say, look I can give you an example right from my own space, the software space. For years we would have product managers, offering managers, maybe interviewing clients, on gut feel deciding what features to put at what priority within the next release. Now we have all these products instrumented behind the scenes with data, so we can literally see the friction points, the exit points, how frequently they come back, how long they're sessions are, we can even see them effectively graduating within the system where they continue to learn, and where they had shorter sessions, they're now going the longer sessions. That's really, really powerful for us in terms of trying to maximize our outcome from a software perspective. So that's where we kind of like, drink our own champagne. >> I got to ask you, so in around 2003, 2004 HBR had an article, front page y'know cover article of how "gut feel beats data and analytics", now this is 2003, 2004, software development as you know it's a lot of art involved, so my question is how are you doing? Is the data informing you in ways that are nonintuitive? And is it driving y'know, business outcomes for IBM? >> It is, look you see, I'll see like GM's of sports teams talking about maybe pushing back a little bit on the data. It's not all data driven, there's a little bit of gut, like is the guy going to, is he a checker in hockey or whatever that happens to be, and I would say, when you actually look at what's going on within baseball, and you look at the data, when you watch baseball growing up, the commentator might say something along the lines of "the pitcher has their stuff" right? "Does the pitcher have their stuff or not?". Now they literally know, the release point based on elevation, IOT within the state of the release point, the spin velocity of the ball, where they mathematically know "does the pitcher have their stuff?", are they hitting their locations? So all that stuff has all become data driven, and if you don't want to embrace it, you get beat, right? I mean even in baseball, I remember talking to one of these Moneyball type guys where I said like "Doesn't weather impact baseball?" And they're like "Yeah, we've looked at that, it absolutely impacts it." 'Cause you always hear of football and remember the old Peyton Manning thing? Don't play Peyton Manning in cold weather, don't bet on Peyton Manning in cold weather. So "I'm like isn't the same in baseball?", And he's like, absolutely it's the same in baseball, players preform different based on the climate. Do any mangers change their lineup based on that? Never. >> Speaking of HBR, I mean in the last few years there was also an article or two by Michael Shrage about the whole notion of real world experimentation and e-commerce, driven by data, y'know in line, to an operational process, like tuning the design iteratively of say, a shopping cart within your e-commerce environment, based on the stats on what work and what does not work. So, in many ways I mean AB testing, real world experimentation thrives on data science. Do you see AB testing becoming a standard business practice everywhere, or only in particular industries like you know, like the Wal-marts of the world? >> Yeah, look so, AB testing, multi-variant testing, they're pervasive, pretty much anyone who has a website ought to be doing this if they're not doing it already. Maybe some startups aren't quite into it. They prioritized in different spots, but mainstream fortune 500 companies are doing this, the tools have made it really easy. I would say, maybe the Achilles heel or the next frontier is, that is effectively saying, kind of creating one pattern of user, putting everyone in a single bucket, right? "Does this button perform better "when it's orange or when it's green? "Oh, it performs better orange." Really, does it perform well for every segmentation orange better than green or is it just a certain segmentation? So that next kind of frontier is going to be, how do we segment it, know a little bit more about you when you're coming in so that AB testing starts to build these kind of sub-profiles, sub-segmentation. >> Micro-segmentation, and of course, the end extreme of that dynamic is one-to-one personalization of experiences and engagements based on knowing 360 degrees about you and what makes you tick as well, so yeah. >> Altshuller: And add onto that context, right? You have your business, let's even keep it really simple, right, you've got your business life, you've got your social life, and your profile of what you're looking for when you're shopping your social life or something is very different than when you're shopping your business life. We have to personalize it to the idea where, I don't want to say schizophrenic but you do have multiple personalities from an online perspective, right? From a digital perspective it all depends in the moment, what is it that you're actually doing, right? And what are you, who are you acting for? >> Marc, I want to ask you, you're homies, your peeps are the business people. >> Yes. >> That's where you spend your time. I'm interested in the relationship between those business people and the data science teams. They're all, we all hear about how data science and unicorns are hard to find, difficult to get the skills, citizen data science is sort of a nirvana. But, how are you seeing businesses bring the domain expertise of the business and blending that with data science? >> So, they do it, I have some cautionary tales that I've experienced in terms of how they're doing it. They feel like, let's just assign the subject matter expert, they'll work with the data scientist, they'll give them context as they're doing their project, but unfortunately what I've seen time and time again, is that subject matter expert right out of the gate brings a tremendous amount of bias based on the types of analysis they've done in the past. >> Vellante: That's not how we do it here. >> Yeah, exactly, like "did you test this?". "Oh yeah, there's no correlation there, we've tried it." Well, just because there's no correlation, as I talked about onstage, doesn't mean it's not part of the pattern in terms of, like you don't want someone in there right off the bat dismissing things. So I always coach, when the business user subject matter experts become involved early, they have to be tremendously open-minded and not all of them can be. I like bringing them in later, because that data scientist, they are unbiased, like they see this data set, it doesn't mean anything to them, they're just numerically telling you what the data set says. Now the business user can then add some context, maybe they grabbed a field that really is an irrelevant field and they can give them that context afterwards. But we just don't want them shutting down, kind of roots, too early in the process. >> You know, we've been talking for a couple of years now within our community about this digital matrix, this digital fabric that's emerged and you're seeing these horizontal layers of technology, whether it's cloud or, you know, security, you all OAuth in with LinkedIn, Facebook, and Twitter. There's a data fabric that's emerging and you're seeing all these new business models, whether it's Uber or Airbnb or WAZE, et cetera, and then you see this blockbuster announcement last week, Amazon buying Whole Foods. And it's just fascinating to us and it's all about the data that a company like an Amazon can be a content company, could be a retail company, now it's becoming a grocer, you see Apple getting into financial services. So, you're seeing industries being able to traverse or companies being able traverse industries and it's all because of the data, so these conversations absolutely are going on in boardrooms. It's all about the digital transformation, the digital disruption, so how do you see, you know, your clients trying to take advantage of that or defend against that? >> Yeah look, I mean, you have to be proactive. You have to be willing to disrupt yourself in all these tech industries, it's just moving too quickly. I read a similar story, I think yesterday, around potentially Blockchain disrupting ridesharing programs, right? Why do you need the intermediary if you have this open ledger and these secure transactions you can do back and forth with this ecosystem. So there's another interesting disruption. Now do the ridesharing guys proactively get into that and promote it, or do they almost in slow motion, get replaced by that at some point. So yeah I think it's a come-on on all of us, like you don't remain a market lead, every market leader gets destructive at some point, the key is, do you disrupt yourself and you remain the market leader, or do you let someone else disrupt you. And if you get disrupted, how quickly can you recover. >> Well you know, you talked to banking executives and they're all talking Blockchain. Blockchain is the future, Bitcoin was designed to disintermediate the bank, so they're many, many banks are embracing it and so it comes back to the data. So my question I have, the discussion I'd like to have is how organizations are valuing data. You can't put data as a value on, y'know an asset on your balance sheet. The accounting industry standards don't exist. They probably won't for decades. So how are companies, y'know crocking data value, is it limiting their ability to move toward a data driven economy, is it a limiting factor that they don't have a good way to value their data, and understand how to monetize it. >> So I have heard of cases where companies have but data on their balance sheet, it's not mainstream at this point, but I mean you've seen it sometimes, and even some bankruptcy proceedings, their industry that's being in a bankruptcy protection where they say "Hey, but this data asset "is really where the value is." >> Vellante: And it's certainly implicit in valuations. >> Correct, I mean you see bios all the time based on the actual data sets, so yeah that data set, they definitely treasure it, and they realize that a lot of their answers are within that data set. And they also I think, understand that they're is a lot of peeling the onion that goes on when you're starting to work through that data, right? You have your initial thoughts, then you correct something based on what the data told you to do, and then the new data comes in based on what your new experience is, and then all of a sudden you have, you see what your next friction point is. You continue to knock down these things, so it is also very iterative working with that data asset. But yeah, these companies are seeing it's very value when they collect the data, but the other thing is the signal of what's driving your business may not be in your data, more and more often it may be in market data that's out there. So you think about social media data, you think about weather data and being able to go and grab that information. I remember watching the show Millions, where they talk about the hedge fund guys running satellites over like Wal-mart parking lots to try to predict the redux for the quarter, right? Like, you're collecting all this data but it's out there. >> Or maybe the value is not so much in the data itself, but in what it enables you to develop as a derivative asset, meaning a statistical predictive model or machine learning model that shows the patterns that you can then drive into, recommendation engines, and your target marketing y'know applications. So you see any clients valuate, doing their valuation of data on those derivative assets? >> Altshuller: Yeah. >> In lieu of... >> In these new business models I see within corporations that have been around for decades, it's actual data offers that they make to maybe their ecosystem, their channel. "Here's data we have, here's how you interpret it, "we'll continue to collect it, we'll continue to curate it, "we'll make it available." And this is really what's driving your business. So yeah, data assets become something that, companies are figuring out how to monetize their data assets. >> Of course those derived assets will decay if those models of, for example machine learning models are not trained with fresh, y'know data from the sources. >> And if we're not testing for new variable too, right? Like if the variable was never in the model, you still have to have this discovery process, that's always going on the see what new variables might be out there, what new data set, right. Like if a new IOT sensor in the baseball stadium becomes available, maybe that one I talked about with elevation of the pitcher, like until you have that you can't use it, but once you have it you have to figure out how to use it. >> Alright lets bring it back to your business, what can I buy from you, what do sell, what are your products? >> Yeah so after being in business analytics is Cognos analytics, Watson analytics, Watts analytics for social media, and planning analytics. Cognos is the "what", what's going on in my business. Watts analytics is the "why", planning analytics is "what do we think is going to happen?". We're starting to do more and more smarter, what do we think's going to happen based on these predictive models instead of just guessing what's going to happen. And then social media really gets into this idea of trying to find the signal, the sentiment. Not just around your own brand, it could be a competitor recall, and what now the intent is of that customer, are they going to now start buying other products, or are they going to stick with the recall company. >> Vellante: Okay so the starting point of your business having Cognos, one of the largest acquisitions ever in IBM's history, and of course it was all about CFO's and reporting and Sarbanes-Oxley was a huge boom to that business, but as I was saying before it, it never really got us to that predictive era. So you're layering those predictive pieces on top. >> That's what you saw on stage. >> Yes, that's right, what, so we saw on stage, and then are you selling to the same constituencies? Or how is constituency that you sell to changing? >> Yeah, no it's actually the same. Well Cognos BI, historically was selling to IT, and Cognos Analytics is selling to the business. But if we take that leap forward then we're now in the market, we have been for a few years now at Cognos Analytics. Yeah, that capability we showed onstage where we talked about not only what's going on, why it's going on, what will happen next, and what we ought to do about it. We're selling that capability for them, the business user, the dashboard becomes like a piece of glass to them. And that glass is able to call services that they don't have to be proficient in, they just want to be able to use them. It calls the weather service, it calls the optimization service, it calls the machine learning data sign service, and it actually gives them information that's forward looking and highly accurate, so they love it, 'cause it's cool they haven't had anything like that before. >> Vellante: Alright Marc Altshuller, thanks very much for coming back on The Cube, it's great to see you. >> Thank you. >> "You can't measure heart" as we say in boston, but you better start measuring. Alright keep right there everybody, Jim and I will right back after this short break. This is The Cube, we're live from Fast Track Your Data in Munich. We'll be right back. (upbeat jingle) (thoughtful music)