>> Hi, and welcome to Data Cloud Catalyst, Women in Tech Round Table Panel Discussion. I am so excited to have three fantastic female executives with me today who have been driving transformation through data throughout their entire career. With me today is Lisa Davis, SVP and CIO of Blue Shield of California. We also have Nishita Henry, who is the Chief Innovation Officer at Deloitte and Theresa Briggs, who is on a variety of board of directors, including our own very own Snowflake. Welcome, ladies. >> Thank you. >> Thank you. >> So I'm just going to dive right in. You all have really amazing careers and resumes behind you. I'm really curious, throughout your career, how have you seen the use of data evolve throughout your career? And, Lisa, I'm going to start with you. >> Thank you. Having been in technology my entire career, technology and data has really evolved from being the province of a few in an organization to frankly being critical to everyone's business outcomes. Now every business leader really needs to embrace data analytics and technology. We've been talking about digital transformation probably the last five, seven years, we've all talked about disrupt or be disrupted. At the core of that digital transformation is the use of data. Data and analytics that we derive insights from and actually improve our decision making by driving a differentiated experience and capability into market. So data has involved as being, I would say, almost tactical in some sense over my technology career, to really being a strategic asset of what we leverage personally in our own careers, but also what we must leverage as companies to drive a differentiated capability to experience and remain relative in the market today. >> Nishita, curious your take on how you've seen data evolve? >> Yeah, I agree with Lisa. It has definitely become the lifeblood of every business, right? It used to be that there were a few companies in the business of technology, every business is now a technology business. Every business is a data business. It is the way that they go to market, shape the market and serve their clients. Whether you're in construction, whether you're in retail, whether you're in healthcare it doesn't matter, right? Data is necessary for every business to survive and thrive. And I remember at the beginning of my career, data was always important but it was about storing data. It was about giving people individual reports, it was about supplying that data to one person or one business unit in silos. And it then evolved right over the course of time into integrating data and to saying, all right, how does one piece of data correlate to the other and how can I get insights out of that data? Now, let's go on to the point of how do I use that data to predict the future? How do I use that data to automate the future? How do I use that data not just for humans to make decisions, but for other machines to make decisions, right? Which is a big leap. And a big change in how we use data, how we analyze data and how we use it for insights in evolving our businesses. >> Yeah, it's really changed so tremendously just in the past five years. It's amazing. So Teresa, we've talked a lot about the Data Cloud, where do you think we're heading with that? And also, how can future leaders really guide their careers in data, especially in those jobs where we don't traditionally think of them in the data science space? Curious your thoughts on that? >> Yeah, well, since I'm on the Snowflake board, I'll talk a little bit about the Snowflake Data Cloud. Now we're getting your company's data out of the silos that exists all over your organization, we're bringing third party data in to combine with your own data, and we're wrapping a governance structure around it and feeding it out to your employees so that they can get their jobs done. And is as simple as that. I think we've all seen the pandemic accelerate the digitization of our work. And if you ever doubted the future of work is here, it is here. And companies are scrambling to catch up by providing the right amount of data, collaboration tools, workflow tools for their workers to get their jobs done. Now, it used to be as prior people have mentioned that in order to work with data you had to be a data scientist. But I was an auditor back in the day and we used to work on 16 columns spreadsheet. And now if you're an accounting major coming out of college joining an auditing firm, you have to be tech and data savvy because you're going to be extracting, manipulating, analyzing and auditing data, that massive amounts of data that sit in your client's IT systems. I'm on the board of Warby Parker, and you might think that their most valuable asset is their amazing frame collection, but it's actually their data, their 360 degree view of the customer. And so if you're a merchant or you're in strategy, or marketing or talent or the co-CEO, you're using data every day in your work. And so I think it's going to become a ubiquitous skill that anyone who's a knowledge worker has to be able to work with data. >> Yeah, I think it's just going to be organic to every role going forward in the industry. So Lisa, curious about your thoughts about Data Cloud, the future of it, and how people can really leverage it in their jobs from future leaders? >> Yeah, absolutely. Most enterprises today are, I would say, hybrid multi cloud enterprises. What does that mean? That means that we have data sitting on prem, we have data sitting in public clouds through software as a service applications, we have a data everywhere, most enterprises have data everywhere. Certainly those that have owned infrastructure or weren't born on the web. One of the areas that I love that Data Cloud is addressing is the area around data portability and mobility. Because I have data sitting in various locations through my enterprise, how do I aggregate that data to really drive meaningful insights out of that data to drive better business outcomes? And at Blue Shield of California, one of our key initiatives is what we call an experienced cube. What does that mean? It means how do I drive transparency of data between providers, members and payers? So that not only do I reduce overhead on providers and provide them a better experience, or hospital systems or doctors, but ultimately, how do we have the member have it their power of their fingertips the value of their data holistically, so that we're making better decisions about their health care? One of the things Teresa was talking about was the use of this data, and I would drive to data democratization. We got to put the power of data into the hands of everyone, not just data scientists. Yes, we need those data scientists to help us build AI models to really drive and tackle these tougher challenges and business problems that we may have in our environments. But everybody in the company, both on the IT side, both on the business side, really need to understand of how do we become a data insights driven enterprise. Put the power of the data into everyone's hands so that we can accelerate capabilities, right? And leverage that data to ultimately drive better business results. So as a leader, as a technology leader, part of our responsibility, our leadership is to help our companies do that. And that's really one of the exciting things that I'm doing in my role now at Blue Shield of California. >> Yeah, it's really, really exciting time. I want to shift gears a little bit and focus on women in tech. So I think in the past five to 10 years, there has been a lot of headway in this space. But the truth is women are still underrepresented in the tech space. So what can we do to attract more women into technology quite honestly. So Nishita, curious, what your thoughts are on that? >> Great question. And I am so passionate about this for a lot of reasons, not the least of which is I have two daughters of my own. And I know how important it is for women and young girls to actually start early in their love for technology, and data and all things digital, right? So I think it's one very important to start early, start an early education, building confidence of young girls that they can do this, showing them role models. We at Deloitte just partnered with Ella the Engineer to actually make comic books centered around young girls and boys in the early elementary age to talk about how heroes and tech solve everyday problems. And so really helping to get people's minds around tech is not just in the back office coding on a computer, tech is about solving problems together that help us as citizens, as customers, right? And as humanity. So I think that's important. I also think we have to expand that definition of tech, as we just said. It's not just about, right? Database design. It's not just about Java and Python coding, it's about design. It's about the human machine interfaces. It's about how do you use it to solve real problems and getting people to think in that kind of mindset makes it more attractive and exciting. And lastly, I'd say look, we have absolute imperative to get a diverse population of people, not just women, but minorities, those with other types of backgrounds, disabilities, etc involved. Because this data is being used to drive decision making, and if we are not all involved, right? In how that data makes decisions, it can lead to unnatural biases that no one intended but can happen just 'cause we haven't involved a diverse enough group of people around it. >> Absolutely. Lisa, curious about your thoughts on this. >> I agree with everything Nishita said. I've been passionate about this area, I think it starts with first we need more role models. We need more role models as women in these leadership roles throughout various sectors. And it really is it starts with us and helping to pull other women forward. So I think certainly, it's part of my responsibility, I think all of us as female executives that if you have a seat at the table to leverage that seat at the table to drive change, to bring more women forward, more diversity forward into the boardroom and into our executive suites. I also want to touch on a point Nishita made about women, we're the largest consumer group in the company yet we're consumers, but we're not builders. This is why it's so important that we start changing that perception of what tech is. And I agree that it starts with our young girls. We know the data shows that we lose our young girls by middle school. Very heavy peer pressure, it's not so cool to be smart, or do robotics, or be good at math and science. We start losing our girls in middle school. So they're not prepared when they go to high school and they're not taking those classes in order to major in the STEM fields in college. So we have to start the pipeline early with our girls. And then I also think it's a measure of what your boards are doing. What is the executive leadership and your goals around diversity and inclusion? How do we invite more diverse population to the decision making table? So it's really a combination of efforts. One of the things that certainly is concerning to me is during this pandemic, I think we're losing one in four women in the workforce now, because of all the demands that our families are having to navigate through this pandemic. The last statistic I saw in the last four months is we've lost 850,000 women in the workforce. This pipeline is critical to making that change in these leadership positions. >> Yeah, it's really a critical time. And now we're coming to the end of this conversation, I want to ask you Teresa, what would be a call to action to everyone listening, both men and women since its needs to be solved by everyone, to address the gender gap in the industry? >> I'd encourage each of you to become an active sponsor. Research shows that women and minorities are less likely to be sponsored than white men. Sponsorship is a much more active form than mentorship. Sponsorship involves helping someone identify career opportunities and actively advocating for them in those roles, opening your network, giving very candid feedback. And we need men to participate too. There are not enough women in tech to pull forward and sponsor the high potential women that are in our pipelines. And so we need you to be part of the solution. >> Nishita real quickly, what would be your call to action to everyone? >> I'd say look around your teams, see who's on them and make deliberate decisions about diversifying those teams. As positions open up, make sure that you have a diverse set of candidates, and make sure that there are women that are part of that team. And make sure that you are actually hiring and putting people into positions based on potential not just experience. >> And real quickly Lisa, will close it out with you, what would your call to action be? >> Well, it's hard to... What Nishita and what Teresa shared I think were very powerful actions. I think it starts with us. Taking action at our own table, making sure you're driving diverse panels and hiring, setting goals for the company. Having your board engaged and holding us accountable and driving to those goals, will help us all see a better outcome but with more women at the executive table and diverse populations. >> Great advice and great action for all of us to take. Thank you all so much for spending time with me today and talking about this really important issue. I really appreciate it. Stay with us.

>> Hi, and welcome to data cloud catalyst women in tech round table panel discussion. I am so excited to have three fantastic female executives with me today who have been driving transformation through data throughout their entire career. With me today is Lisa Davis SVP and CIO of Blue Shield of California. We also have Nishita Henry who is the chief innovation officer at Deloitte and Teresa Briggs, who is on a variety of board of directors, including our very own Snowflake. Welcome, ladies. >> Thank you. So I'm just going to dive right in. You all have really amazing careers and resumes behind you. I'm really curious, throughout your career, how have you seen the use of data evolve throughout your career? And Lisa, I'm going to start with you. >> Thank you. Having been in technology my entire career, technology and data has really evolved from being the province of a few in an organization to frankly being critical to everyone's business outcomes. But now every business leader really needs to embrace data analytics and technology. We've been talking about digital transformation probably the last five, seven years. We've all talked about disrupt or be disrupted. At the core of that digital transformation is the use of data, data, and analytics that we derive insights from and actually improve our decision-making by driving a differentiated experience and capability into market. So data has involved as being, I would say, almost tactical in some sense over my technology career to really being a strategic asset of what we leveraged personally in our own careers, but also what we must leverage as companies to drive a differentiated capability to experience and remain relative in the market today. >> Nishita curious your take on, how you've seen data evolve? >> Yeah, I agree with Lisa, it has definitely become the lifeblood of every business, right? It used to be that there were a few companies in the business of technology. Every business is now a technology business. Every business is a data business. It is the way that they go to market, shape the market and serve their clients. Whether you're in construction, whether you're in retail, whether you're in healthcare doesn't matter, right? Data is necessary for every business to survive and thrive. And I remember at the beginning of my career, data was always important, but it was about storing data. It was about giving people individual reports. It was about supplying that data to one person or one business unit in silos. And it then evolved right over the course of time and to integrating data and to saying, all right, how does one piece of data correlate to the other? And how can I get insights out of that data? Now let's go on to the point of how do I use that data to predict the future? How do I use that data to automate the future? How do I use that data not just for humans to make decisions but for other machines to make decisions, right? Which is a big leap and a big change in how we use data, how we analyze data and how we use it for insights and evolving our businesses. >> Yeah. It's really changed so tremendously, just in the past five years, it's amazing. So Teresa, we've talked a lot about the data cloud, where do you think we're heading with that? And also how can future leaders really guide their careers in data, especially in those jobs where we don't traditionally think of them in the data science space, curious your thoughts on that. >> Yeah. Well, since I'm on the Snowflake board, I'll talk a little bit about the Snowflake data cloud that we're getting your company's data out of the silos that exist all over your organization. We're bringing third party data in to combine with your own data and we're wrapping a governance structure around it and feeding it out to your employees so that they can get their jobs done. And it's as simple as that, I think we've all seen the pandemic accelerated the digitization of our work. And if you ever doubted that the future of work is here, it is here. And companies are scrambling to catch up by providing the right amount of data, collaboration tools, workflow tools for their workers to get their jobs done. Now it used to be, as prior, people have mentioned that in order to work with data, you had to be a data scientist. But I was an auditor back in the day and we used to work on 16 columns spreadsheet. And now if you're an accounting major coming out of college, joining an auditing firm, you have to be tech and data savvy because you're going to be extracting, manipulating, analyzing, and auditing data. That massive amounts of data that sit in your client's IT systems. I'm on the board of Warby Parker. And you might think that their most valuable asset is their amazing frame collection but it's actually their data. There are 360 degree view of the customer. And so if you're a merchant or you're in strategy or marketing or talent or the co-CEO, you're using data every day in your work. And so I think it's going to become a ubiquitous skill that any anyone who's a knowledge worker has to be able to work with data. >> Now, I think it's just going to be organic to every role going forward in the industry. >> So Lisa curious about your thoughts about data cloud, the future of it, and how people can really leverage it in their jobs from future leaders. >> Yeah, absolutely. Most enterprises today are, I would say, hybrid multi-cloud enterprises. What does that mean? That means that we have data sitting on prem. We have data sitting in public clouds through software, as a service applications. We have a data everywhere. Most enterprises have data everywhere. Certainly those that have owned infrastructure or weren't born on the web. One of the areas that I'd love that data cloud is addressing is the area around data portability and mobility. Because I have data sitting in various locations through my enterprise, how do I aggregate that data to really drive meaningful insights out of that data to drive better business outcomes. And at Blue Shield of California, one of our key initiatives is what we call an experience cube. What does that mean? It means how do I drive transparency of data between providers and members and payers so that not only do I reduce overhead on providers and provide them a better experience or hospital systems or doctors, but ultimately how do we have the member have at their power of their fingertips the value of their data holistically so that we're making better decisions about their healthcare? One of the things Teresa was talking about was the use of this data. And I would drive to data democratization. We got to put the power of data into the hands of everyone, not just data scientists. Yes, we need those data scientists to help us build AI models to really drive and tackle these tougher challenges and business problems that we may have in our environments. But everybody in the company, both on the IT side, both on the business side, really need to understand of how do we become a data insights driven enterprise, put the power of the data into everyone's hands so that we can accelerate capabilities, right? And leverage that data to ultimately drive better business results. So as a leader, as a technology leader, part of our responsibility, our leadership is to help our companies do that. And that's really one of the exciting things that I'm doing in my role now at Blue Shield of California. >> Yeah. It's really, really exciting time. I want to shift gears a little bit and focus on women in tech. So I think in the past 5 to 10 years there has been a lot of headway in this space but the truth is women are still underrepresented in the tech space. So what can we do to attract more women into technology? Quite honestly. So Nishita curious what your thoughts are on that? >> Great question. And I am so passionate about this for a lot of reasons, not the least of which is I have two daughters of my own and I know how important it is for women and young girls to actually start early in their love for technology and data and all things digital, right? So I think it's one very important to start early, starting early education, building confidence of young girls that they can do this, showing them role models. We at Deloitte just partnered with LOV engineer to actually make comic books centered around young girls and boys in the early elementary age to talk about how heroes in techs solve everyday problems. And so really helping to get people's minds around tech is not just in the back office, coding on a computer, tech is about solving problems together that help us as citizens as customers, right? And as humanity. So I think that's important. I also think we have to expand that definition of tech as we just said, it's not just about database design. It's not just about Java and Python coding. It's about design, it's about the human machine interfaces. It's about how do you use it to solve real problems and getting people to think in that kind of mindset makes it more attractive and exciting. And lastly, I'd say, look we have a absolute imperative to get a diverse population of people, not just women but minorities, those with other types of backgrounds, disabilities, et cetera, involved because this data is being used to drive decision-making, and if we're all involved and how that data makes decisions, it can lead to unnatural biases that no one intended but can happen just 'cause we haven't involved a diverse enough group of people around it. >> Absolutely. Lisa, I'm curious about your thoughts on this. >> Oh, I agree with everything Nishita said. I've been passionate about this area. I think it starts with first, we need more role models. We need more role models as women in these leadership roles throughout various sectors. And it really is, it starts with us and helping to pull other women forward. So I think it certainly it's part of my responsibility. I think all of us as female executives that if you have a seat at the table to leverage that seat at the table to drive change to bring more women forward, more diversity forward into the boardroom and into our executive suites. I also want to touch on a point Nishita made about women. We're the largest consumer group in the company yet we're consumers, but we're not builders. This is why it's so important that we start changing that perception of what tech is. And I agree that it starts with our young girls. We know the data shows that we lose our young girls by middle school, very heavy peer pressure. It's not so cool to be smart or do robotics or be good at math and science. We start losing our girls in middle school. So they're not prepared when they go to high school and they're not taking those classes in order to major in these STEM fields in college. So we have to start the pipeline early with our girls. And then I also think it's a measure of what your boards are doing. What is the executive leadership and your goals around diversity and inclusion? How do we invite more diverse population to the decision-making table? So it's really a combination of efforts. One of the things that certainly is concerning to me is during this pandemic, I think we're losing one in four women in the workforce now because of all the demands that our families are having to navigate through this pandemic. The last statistic I saw in the last four months is we've lost 850,000 women in the workforce. This pipeline is critical to making that change in these leadership positions. >> Yeah, it's really a critical time. And now we're coming to the end of this conversation. I want to ask you Teresa, what would be a call to action to everyone listening, both men and women since it needs to be solved by everyone to address the gender gap in the industry. >> I'd encourage to you to become an active sponsor. Research shows that women and minorities are less likely to be sponsored than white men. Sponsorship is a much more active form than mentorship. Sponsorship involves helping someone identify career opportunities and actively advocating for them in those roles, opening your network, giving very candid feedback. And we need men to participate too. There are not enough women in tech to pull forward and sponsor the high potential women that are in our pipelines. And so we need you to be part of the solution. >> Nishita, real quickly, what would be your call to action to everyone? >> I'd say, look around your teams, see who's on them and make deliberate decisions about diversifying those teams, as positions open up, make sure that you have a diverse set of candidates. Make sure that there are women that are part of that team and make sure that you are actually hiring and putting people into positions based on potential, not just experience. >> And real quickly, Lisa, we'll close it out with you. What would your call to action be? >> Well, it's hard to, but Nishita and what Teresa shared, I think were very powerful actions. I think it starts with us taking action at our own table, making sure you're driving diverse panels and hiring, setting goals for the company, having your board engaged and holding us accountable and driving to those goals will help us all see a better outcome with more women at the executive table and diverse populations. >> So I want to talk to you all about a pivotal moment in your career. It could have been a mentorship. It could have been maybe a setback in your career or maybe a time that you really took a risk and it paid off big, something that really helped define your career going forward. Curious what those moments were for you all in your career. Teresa, we'll start with you. >> Sure. I had a great sponsor and he was a white male by the way. He identified some potential in me when I was early in my career about five years in and he really helped pave the way for a number of decisions I made along the way to take different roles in the firm. I was at Deloitte, he's still in my life today. We get together a couple of times a year. And even though we're both retired from Deloitte, we still have that relationship and what that tell me was how to be a great sponsor. And so one of the most satisfying things I did in my career was when I finally got to the place where I was no longer reaching for the next rank of the ladder for myself, I got to turn around and pull through all of these amazing future leaders into roles that were going to help them accelerate their careers. >> What about you, Lisa? >> I think there's been many of those moments. One I'll speak about is having spin 20, 25 years in technology, I had spent my first career in department of defense, moved over to academia and then went to a high-tech firm on their IT side, really in hopes of getting the CIO role having been a CIO, I did not get the CIO role, and really had a decision to make. One of the opportunities that was presented to me was to move to the business side to run a $9 billion P&L on one of the core business units within the company. And of course, I was terrified. It was a very risky decision having never run a P&L before and not starting small going right to the billion dollar mark in terms of (laughs) what that would look like. And frankly decided to seize that opportunity and I've certainly learned in my career that those opportunities that really push you out of your comfort zone that take you down a really completely different path or where the greatest opportunities for growth and learning occur. So I did that role for three and a half years before coming into my current role back to a CIO role at Blue Shield of California in healthcare, and just a tremendous amount of learning, having been on the business side and managing a P&L that I now apply to how I engage with my partners at Blue Shield. >> I couldn't agree more. I think forcing yourself out of that comfort zone is so critical for learning and driving your career for sure. Nishita, what about you? >> Yeah, I agree. Lots of pivotal moments, but I'll talk about one very early in my career, actually was an intern and one of my responsibilities was to help research back then facial recognition technology. And I had to go out there and evaluate vendors and take meetings with vendors and figure out, all right, which ones do we want to actually test? And I remember I was leading a meeting, two of my kind of supervisors were with us. And I know I went through the list of questions and then the meeting kind of ended. And I didn't speak up at that point in time to kind of say here are the next steps or here's what I recommend. I kind of looked at my supervisors to do that. Just assuming they should be wrapping it up and they should be the ones to make a final decision or choice. And after that meeting, he came to me and he's like you know Nishita you did a really nice job in bringing these technologies forward but I wish you would have spoken up because you're the one who've done the most research. And you're the one who has the most background on what we should do next. Next time don't stand by and let someone else be your voice. And it was so powerful for me and I realized, wow, I should have more confidence in myself to be able to actually use my voice and do what I was asked to do versus leave it to someone else because I assumed that I was too junior or I assumed I didn't have enough experience. So that was really pivotal for me early in my career to learn how to use my voice. >> I'm really curious for you, Nishita. What drew you to the industry of data? What was something when you were young that drew you into that space? >> Yeah. So my background is actually in engineering and it's actually funny. It's an electrical engineering and I probably couldn't do another thermal dynamics equation to save my life anymore (laughs). But what drew me to technology was problem solving, right? It was all about how do I take a bunch of data and information and create a new solution, right? Whether it was, how do I create a device? I remember in college, right? Creating a device to go down stadium steps and clean, right? How do I take data for how this machine will interact with the environment in order to create it? So I always viewed it as problem solving and that's what has always attracted me into the field. >> That's great. So, Teresa, I'm curious, at what point did you feel that you really found your voice in your career, in yourself as a part of your professional life? >> Yeah. About 12 years into my career I started working as an M&A partner and I was working with a private equity firm along with their lawyers and other advisors, bankers and so forth. And what I realized in that situation was that I was the expert in what I did. And so, I mean, I found my voice before that in many other ways but that was sort of a moment where I felt like, "I'm here to deliver an expertise to this group of people. And none of them have the expertise that I have. And so I need to just stand firm in my shoes and deliver that expertise with confidence." So that was my example. >> That's great. Well, Lisa, what about you? What was that moment that you felt that you just found your voice kind of in your groove and that confidence kicked in? >> No, I don't know if it was exactly a moment but it was certainly a realization. Right out of college, I was working for the federal government in department of defense and certainly male dominated. And through that realized that to be heard, I had to become very good at what I do. So I built that confidence, frankly, by delivering results and capability and becoming an expert in the work, essentially the services that I provide. And when you become very good at what you do, regardless of what you look like, then people will start to listen. So I think it starts with delivering results. I think you have to build your confidence and through that you find to use your voice so that you are being heard, having worked in department of defense and academia and high tech, I've had to leverage that throughout my entire career ultimately for my voice to be heard, and to be represented within the roles that I was playing. >> That's great. I know one of the things that we've also talked about is just the value, the business value, the importance of having a diverse workforce and a diverse team and the value that that brings to the outcomes. What are some of your strategies to create those types of teams? What, as leaders in your company, you manage a team and what is your advice to them, your strategies to get a diverse pool of candidates and a diverse team. Nishita, what about you? >> I think it's looking beyond what the individual role is, right? So a lot of times we have a role description and you want these certain skills and so (indistinct), or you get a certain set of candidates. I think it's taking a step back and saying, "What are the objectives of my team? What am I trying to accomplish? What types of business acumen do I need on that team? What types of tech acumen, what types of personalities? Do I want people who know how to work with others and therefore bring them together? Do I need people who are also drivers and know how to get things done, right?" It's finding the right chemistry. We have a business chemistry, talk track around. We don't need all different kinds to make a really good team. So I think it's taking a step back and understanding what you need the makeup of your team to be, understanding the hard skills and the soft skills. And then thinking about what are all the sources you could really go to for them and being a little bit non-traditional and saying, "Do I need a full-time person all the time to do this job that's sitting here? Can I be more diverse in finding people from the crowd? Can I have part-time resources? Can I use different pieces and parts of the ecosystem to actually bring together the full team that represents the diversity?" It's just expanding our mind and stop thinking about a role to person, start thinking about it as the makeup of a team, to the outcome you desire. >> It's really about being creative and just thinking in new ways. Teresa, I'm super curious, since you sit on a bunch of different boards, what kind of strategies do you see companies taking to attract different talent? >> So I can address that from the board lens, for sure. And boards are probably one of the least diverse bodies in business right now, but that is changing, and for the better, obviously they were traditionally kind of white male dominated. And then we've had this wave of women joining boards. And now we're starting to see a wave of diverse individuals join boards. And with each person who's diverse that joins a board that I'm on, the dynamic of the discussion changes because they bring a different perspective. They bring a different way of thinking. They came from a different background or a different functional skillset or a different geography or you name, whatever element of diversity you want to see. We just added the head of Apple music to the service in our board. And so you might scratch your head and say, "Wow, the head of Apple music and an enterprise software company that is a B2B software company." But he thinks deeply about how the end user consumes in his case content and in our case software. And so he's able to bring just a completely different perspective to the discussion we have at the board table. And I think at the end of the day, that's what diversity is all about, is improving the outcome of whatever it is. If you're producing something or making important decisions like we do in board rooms. >> That's amazing. Lisa, real quickly, what are some of your strategies? >> Yeah. Well, we know diverse teams actually produce better business results. So there's no reason, there's absolutely no reason why we shouldn't think in that lens. I think it starts with our hiring and the makeup of our teams. I think it requires more than creativity though. You have to be very purposeful. I'm in the process of hiring four leadership positions on my team. And it's really to me, almost like a puzzle piece of diverse perspectives and knowledge and capabilities that come together that ultimately create a high performing team. But I can't tell you how many times I got to go back to HR and say, "I need to see more diverse talent. Are there any more women in the pool?" One of the things we've struggled, we have to get more women into the roles is, and we heard this from Sheryl Sandberg, as women, we feel we need to meet every qualification on an application. Whereas men, "I got a couple I'm good to go." And they throw their name in the hat. They take much more risk than we do as women. So we need to encourage our women to get out of your comfort zone. You don't need to meet every qualification. What Nishita was saying of thinking more broadly about what this role requires and the type of individual that we're looking for, but be purposeful in terms of driving to diversity as our end result. >> That is so true. What you just said. Thank you so much for sharing your insights. It's really interesting to hear all your strategies and thanks for sharing. >> And you're clear.

>> Hi and welcome to Data Cloud catalyst Women in Tech Round Table Panel discussion. I am so excited to have three fantastic female executives with me today, who have been driving transformations through data throughout their entire career. With me today is Lisa Davis, SVP and CIO OF Blue shield of California. We also have Nishita Henry who is the Chief Innovation Officer at Deloitte and Teresa Briggs who is on a variety of board of directors including our very own Snowflake. Welcome ladies. >> Thank you. >> So I am just going to dive right in, you all have really amazing careers and resumes behind you, am really curious throughout your career, how have you seen the use of data evolve throughout your career and Lisa am going to start with you. >> Thank you, having been in technology my entire career, technology and data has really evolved from being the province of a few in an organization to frankly being critical to everyone's business outcomes. Now every business leader really needs to embrace data analytics and technology. We've been talking about digital transformation, probably the last five, seven years, we've all talked about, disrupt or be disrupted, At the core of that digital transformation is the use of data. Data and analytics that we derive insights from and actually improve our decision making by driving a differentiated experience and capability into market. So data has involved as being I would say almost tactical, in some sense over my technology career to really being a strategic asset of what we leverage personally in our own careers, but also what we must leverage as companies to drive a differentiated capability to experience and remain relative in the market today. >> Nishita curious your take on, how you have seen data evolve? >> Yeah, I agree with Lisa, it has definitely become a the lifeblood of every business, right? It used to be that there were a few companies in the business of technology, every business is now a technology business. Every business is a data business, it is the way that they go to market, shape the market and serve their clients. Whether you're in construction, whether you're in retail, whether you're in healthcare doesn't matter, right? Data is necessary for every business to survive and thrive. And I remember at the beginning of my career, data was always important, but it was about storing data, it was about giving people individual reports, it was about supplying that data to one person or one business unit in silos. And it then evolved right over the course of time into integrating data into saying, alright, how does one piece of data correlate to the other and how can I get insights out of that data? Now, its gone to the point of how do I use that data to predict the future? How do I use that data to automate the future? How do I use that data not just for humans to make decisions, but for other machines to make decisions, right? Which is a big leap and a big change in how we use data, how we analyze data and how we use it for insights and involving our businesses. >> Yeah its really changed so tremendously just in the past five years, its amazing. So Teresa we've talked a lot about the Data Cloud, where do you think we are heading with that and also how can future leaders really guide their careers in data especially in those jobs where we don't traditionally think of them in the data science space? Teresa your thoughts on that. >> Yeah, well since I'm on the Snowflake Board, I'll talk a little bit about the Snowflake Data Cloud, we're getting your company's data out of the silos that exist all over your organization. We're bringing third party data in to combine with your own data and we're wrapping a governance structure around it and feeding it out to your employees so they can get their jobs done, as simple as that. I think we've all seen the pandemic accelerate the digitization of our work. And if you ever doubted that the future of work is here, it is here and companies are scrambling to catch up by providing the right amount of data, collaboration tools, workflow tools for their workers to get their jobs done. Now, it used to be as prior people have mentioned that in order to work with data you had to be a data scientist, but I was an auditor back in the day we used to work on 16 column spreadsheets. And now if you're an accounting major coming out of college joining an auditing firm, you have to be tech and data savvy because you're going to be extracting, manipulating, analyzing and auditing data, that massive amounts of data that sit in your clients IT systems. I'm on the board of Warby Parker, and you might think that their most valuable asset is their amazing frame collection, but it's actually their data, their 360 degree view of the customer. And so if you're a merchant, or you're in strategy, or marketing or talent or the Co-CEO, you're using data every day in your work. And so I think it's going to become a ubiquitous skill that any anyone who's a knowledge worker has to be able to work with data. >> Yeah I think its just going to be organic to every role going forward in the industry. So, Lisa curious about your thoughts about Data Cloud, the future of it and how people can really leverage it in their jobs for future leaders. >> Yeah, absolutely most enterprises today are, I would say, hybrid multicloud enterprises. What does that mean? That means that we have data sitting on-prem, we have data sitting in public clouds through software as a service applications. We have a data everywhere. Most enterprises have data everywhere, certainly those that have owned infrastructure or weren't born on the web. One of the areas that I love that Data Cloud is addressing is area around data portability and mobility. Because I have data sitting in various locations through my enterprise, how do I aggregate that data to really drive meaningful insights out of that data to drive better business outcomes? And at Blue Shield of California, one of our key initiatives is what we call an Experienced Cube. What does that mean? That means how do I drive transparency of data between providers, members and payers? So that not only do I reduce overhead on providers and provide them a better experience, our hospital systems are doctors, but ultimately, how do we have the member have it their power of their fingertips the value of their data holistically, so that we're making better decisions about their health care. One of the things Teresa was talking about, was the use of this data and I would drive to data democratization. We got to put the power of data into the hands of everyone, not just data scientists, yes we need those data scientists to help us build AI models to really drive and tackle these tough old, tougher challenges and business problems that we may have in our environments. But everybody in the company both on the IT side, both on the business side, really need to understand of how do we become a data insights driven enterprise, put the power of the data into everyone's hands so that we can accelerate capabilities, right? And leverage that data to ultimately drive better business results. So as a leader, as a technology leader, part of our responsibility, our leadership is to help our companies do that. And that's really one of the exciting things that I'm doing in my role now at Blue Shield of California. >> Yeah its really, really exciting time. I want to shift gears a little bit and focus on women in Tech. So I think in the past five to ten years there has been a lot of headway in this space but the truth is women are still under represented in the tech space. So what can we do to attract more women into technology quite honestly. So Nishita curious what your thoughts are on that? >> Great question and I am so passionate about this for a lot of reasons, not the least of which is I have two daughters of my own and I know how important it is for women and young girls to actually start early in their love for technology and data and all things digital, right? So I think it's one very important to start early started early education, building confidence of young girls that they can do this, showing them role models. We at Deloitte just partnered with LV Engineer to actually make comic books centered around young girls and boys in the early elementary age to talk about how heroes in tech solve everyday problems. And so really helping to get people's minds around tech is not just in the back office coding on a computer, tech is about solving problems together that help us as citizens, as customers, right? And as humanity, so I think that's important. I also think we have to expand that definition of tech, as we just said it's not just about right, database design, It's not just about Java and Python coding, it's about design, it's about the human machine interfaces, it's about how do you use it to solve real problems and getting people to think in that kind of mindset makes it more attractive and exciting. And lastly, I'd say look we have a absolute imperative to get a diverse population of people, not just women, but minorities, those with other types of backgrounds, disabilities, et cetera involved because this data is being used to drive decision making in all involved, right, and how that data makes decisions, it can lead to unnatural biases that no one intended but can happen just 'cause we haven't involved a diverse enough group of people around it. >> Absolutely, lisa curious about your thoughts on this. >> I agree with everything Nishita said, I've been passionate about this area, I think it starts with first we need more role models, we need more role models as women in these leadership roles throughout various sectors. And it really is it starts with us and helping to pull other women forward. So I think certainly it's part of my responsibility, I think all of us as female executives that if you have a seat at the table to leverage that seat at the table to drive change, to bring more women forward more diversity forward into the boardroom and into our executive suites. I also want to touch on a point Nishita made about women we're the largest consumer group in the company yet we're consumers but we're not builders. This is why it's so important that we start changing that perception of what tech is and I agree that it starts with our young girls, we know the data shows that we lose our like young girls by middle school, very heavy peer pressure, it's not so cool to be smart, or do robotics, or be good at math and science, we start losing our girls in middle school. So they're not prepared when they go to high school, and they're not taking those classes in order to major in these STEM fields in college. So we have to start the pipeline early with our girls. And then I also think it's a measure of what your boards are doing, what is the executive leadership in your goals around diversity and inclusion? How do we invite more diverse population to the decision making table? So it's really a combination of efforts. One of the things that certainly is concerning to me is during this pandemic, I think we're losing one in four women in the workforce now because of all the demands that our families are having to navigate through this pandemic. The last statistic I saw in the last four months is we've lost 850,000 women in the workforce. This pipeline is critical to making that change in these leadership positions. >> Yeah its really a critical time and now we are coming to the end of this conversation I want to ask you Teresa what would be a call to action to everyone listening both men and women since its to be solved by everyone to address the gender gap in the industry? >> I'd encourage each of you to become an active sponsor. Research shows that women and minorities are less likely to be sponsored than white men. Sponsorship is a much more active form than mentorship. Sponsorship involves helping someone identify career opportunities and actively advocating for them and those roles opening your network, giving very candid feedback. And we need men to participate too, there are not enough women in tech to pull forward and sponsor the high potential women that are in our pipelines. And so we need you to be part of the solution. >> Nishita real quickly what would be your call to action to everyone? >> I'd say look around your teams, see who's on them and make deliberate decisions about diversifying those teams, as positions open up, make sure that you have a diverse set of candidates, make sure that there are women that are part to that team and make sure that you are actually hiring and putting people into positions based on potential not just experience. >> And real quickly Lisa, we'll close it out with you what would your call to action be? >> Wow, it's hard to what Nishita and what Tricia shared I think we're very powerful actions. I think it starts with us. Taking action at our own table, making sure you're driving diverse panels and hiring setting goals for the company, having your board engaged and holding us accountable and driving to those goals will help us all see a better outcome with more women at the executive table and diverse populations. >> Great advice and great action for all of us to take. Thank you all so much for spending time with me today and talking about this really important issue, I really appreciate it. Stay with us.

>> Narrator: Live from Las Vegas, it's theCUBE, covering AWS re:Invent 2017, presented by AWS, Intel, and our ecosystem of partners. >> Hello everyone, welcome to a special CUBE presentation here, live in Las Vegas for Amazon Web Service's AWS re:Invent 2017. This is theCUBE's fifth year here. We've been watching the progression. I'm John Furrier with Justin here as my co-host. Our two next guests are Bob Rogers, the chief data scientist at Intel, and Julie Cardoa, who's the CEO of Thorn. Great guests, showing some AI for good. Intel, obviously, good citizen and great technology partner. Welcome to theCUBE. >> Thank you, thanks for having us! >> So, I saw your talk you gave at the Public Sector Breakfast this morning here at re:Invent. Packed house, fire marshal was kicking people out. Really inspirational story. Intel, we've talked at South by Southwest. You guys are really doing a lot of AI for good. That's the theme here. You guys are doing incredible work. >> Julie: Thank you. >> Tell your story real quick. >> Yeah, so Thorn is a nonprofit, we started about five years ago, and we are just specifically dedicated to build new technologies to defend children form sexual abuse. We were seeing that, as, you know, new technologies emerge, there's new innovation out there, how child sexual abuse was presenting itself was changing dramatically. So, everything from child sex trafficking online, to the spread of child sexual abuse material, livestreaming abuse, and there wasn't a concentrated effort to put the best and brightest minds and technology together to be a part of the solution, and so that's what we do. We build products to stop child abuse. >> John: So you're a nonprofit? >> Julie: Yep! >> And you're in that public sector, but you guys have made a great progress. What's the story behind it? How did you get to do so effective work in such a short period of time as a nonprofit? >> Well, I think there's a couple things to that. One is, well, we learned a lot really quickly, so what we're doing today is not what we thought we would do five years ago. We thought we were gonna talk to big companies, and push them to do more, and then we realized that we actually needed to be a hub. We needed to build our own engineering teams, we needed to build product, and then bring in these companies to help us, and to add to that, but there had to be some there there, and so we actually have evolved. We're a nonprofit, but we are a product company. We have two products used in 23 countries around the world, stopping abuse every day. And I think the other thing we learned is that we really have to break down silos. So, we didn't, in a lot of our development, we didn't go the normal route of saying, okay, well this is a law enforcement job, so we're gonna go bid for a big government RFE. We just went and built a tool and gave it to a bunch of police officers and they said, "Wow, this works really well, "we're gonna keep using it." And it kinda spread like wildfire. >> And it's making a difference. It's really been a great inspirational story. Check out Thorn, amazing work, real use case, in my mind, a testimonial for how fast you can accelerate. Congratulations. Bob, I wanna get your take on this because it's a data problem that, actually, the technology's applying to a problem that people have been trying to crack the code on for a long time. >> Yeah, well, it's interesting, 'cause the context is that we're really in this era of AI explosion, and AI is really computer systems that can do things that only humans could do 10 years ago. That's kind of my basic way of thinking about it, so the problem of being able to recognize when you're looking at two images of the same child, which is the piece that we solved for Thorn, actually, you know, is a great example of using the current AI capabilities. You start with the problem of, if I show an algorithm two different images of the same child, can it recognize that they're the same? And you basically customize your training to create a very specific capability. Not a basic image recognition or facial recognition, but a very specific capability that's been trained with specific examples. I was gonna say something about what Julie was describing about their model. Their model to create that there there has been incredible because it allows them to really focus our energy into the right problems. We have lots of technology, we have lots of different ways of doing AI and machine learning, but when we get a focus on this is the data, this is the exact problem we need to solve, and this is the way it needs to work for law enforcement, for National Center for Missing and Exploited Children. It has really just turned the knob up to 11, so to speak. >> I mean, this is an example where, I mean, we always talk about how tech transformation can make things go faster. It's such an obvious problem. I mean, it's almost everyone kinda looks away because it's too hard. So, I wanna ask you, how do people make this happen for other areas for good? So, for instance, you know, what was the bottlenecks before? What solved the problem, because, I mean, you could really make a difference here. You guys are. >> Well, I think there's a couple things. I think you hit on one, which is this is a problem people turn away from. It's really hard to look at. And the other thing is is there's not a lot of money to be made in using advanced technology to find missing and exploited children, right? So, it did require the development of a nonprofit that said, "We're gonna do this, "and we're gonna fundraise to get it done." But it also required us to look at it from a technology angle, right? I think a lot of times people look at social issues from the impact angle, which we do, but we said, "What if we looked at it "from a different perspective? "How can technology disrupt in this area?" And then we made that the core of what we do, and we partnered with all the other amazing organizations that are doing the other work. And I think, then, what Bob said was that we created a hub where other experts could plug into, and I think, in any other issue area that you're working on, you can't just talk about it and convene people. You actually have to build, and when you build, you create a platform that others can add to, and I think that is one of the core reasons why we have seen so much progress, is we started out convening and really realized that wasn't gonna last very long, and then we built, and once we started building, we scaled. >> So, you got in the market quickly with something. >> Yeah. >> So, one of the issues with any sort of criminal enterprise is it tends to end up in a bit of an arms race, so you've built this great technology but then you've gotta keep one step ahead of the bad guys. So, how are you actually doing that? How are you continuing to invest in this and develop it to make sure that you're always one step ahead? >> So, I can address that on a couple of levels. One is, you know, working with Thorn, and I lead a program at Intel called the Safer Children Program, where we work with Thorn and also the National Center for Missing and Exploited Children. Those conversations bring in all of the tech giants, and there's a little bit of sibling rivalry. We're all trying to throw in our best tech. So, I think we all wanna do as well as we can for these partnerships. The other thing is, just in very tactical terms, working with Thorn, we've actually, Thorn and with Microsoft, we've created a capability to crowdsource more data to help improve the accuracy of these deep learning algorithms. So, by getting critical mass around this problem, we've actually now created enough visibility that we're getting more and more data. And as you said earlier, it's a data problem, so if you have enough data, you can actually create the models with the accuracy and the capability that you need. So, it starts to feed on itself. >> Julie talked about the business logic, how she attacked that. That's really, 'cause I think one thing notable, good use case, but from a tech perspective, how does the cloud fit in with Intel specifically? Because it really, the cloud is an enabler too. >> Bob: Yeah, absolutely. >> How's that all working with Intel? And you go on about whole new territory you guys are forging in here, it's awesome, but the cloud. >> Right, so, for us, the cloud is an incredible way for us to make our compute capability available to anyone who needs to do computing, especially in this data-driven algorithm era where more and more machine learning, more and more AI, more and more data-driven problems are coming to the fore, doing that work on the cloud and being able to scale your work according to how much data is coming in at any time, it makes the cloud a really natural place for us. And of course, Intel's hardware is a core component of pretty much all the cloud that you could connect to. >> And the compute that you guys provide, and Amazon adds to it, their cloud is impressive. Now, I'd like to know what you guys are gonna be talking about in your session. You have a session here at re:Invent. What's the title of the session, what's the agenda, is it the same stuff here, what's gonna be talked about? >> So, we're talking about life-changing AI applications, and in specific we're gonna talk about, at the end Julie will talk about what Thorn has done with the child-finder and the AI that we and Microsoft built for them. We'll also, I'll start out by talking about Intel's role broadly in the computing and AI space. Intel really looks to take all of its different hardware, and networking, and memory assets, and make it possible for anybody to do the kinds of artificial intelligence or machine learning they need to do. And then in the middle, there's a really cool deployment on AWS sandwich that (something) will talk about how they've taken the models and really dialed them up in terms of how fast you can go through this data, so that we can go through millions and millions of images in our searches, and come back with results really, really fast. So, it's a great sort of three piece story about the conception of AI, the deployment at scale and with high performance, and then how Thorn is really taking that and creating a human impact around it. >> So, Bob, I asked you the Intel question because no one calls up Intel and says, "Hey, give me some AI for good." I mean, I wish that would be the case. >> Well, they do now. >> If they do, well, share your strategy, because cloud makes sense. I could see how you could provision easily, get in there, really empowering people to do stuff that's passionable and relevant. But how do you guys play in all of this? 'Cause I know you supply stuff to the cloud guys. Is this a formal program you're doing at Intel? Is this a one-off? >> Yeah, so Safer Children is a formal program. It started with two other folks, Lisa Davis and Lisa Theinai, going to the VP of the entire data center group and saying, "There is an opportunity to make a big impact "with Intel technology, and we'd like to do this." And it started literally because Intel does actually want to do good work for humankind, and frankly, the fact that these people are using our technology and other technology to hurt children, it steams our dumplings, frankly. So, it started with that. >> You've been a team player with Amazon and everyone else. >> Exactly, so then, once we've been able to show that we can actually create technology and provide infrastructure to solve these problems, it starts to become a self-fulfilling prophecy where people are saying, "Hey, we've got this "interesting adjacent problem that "this kind of technology could solve. "Is there an opportunity to work together and solve that?" And that fits into our bigger, you know, people ask me all the time, "Why does Intel have a chief data scientist?" We're a hardware company, right? The answer is-- >> That processes a lot of data! >> Yes, that processes a lot of data. Literally, we need to help people know how to get value from their data. So, if people are successful with their analytics and their AI, guess what, they're gonna invest in their infrastructure, and it sort of lifts Intel's boat across the board. >> You guys have always been a great citizen, and great technology provider, and hats off to Intel. Julie, tell a story about an example people can get a feel for some of the impact, because I saw you on stage this morning with Theresa Carlson, and we've been tracking her efforts in the public sector have been amazing, and Intel's been part of that too, congratulations. But you were kind of emotional, and you got a lot of applause. What's some of the impact? Tell a story of how important this really is, and your work at Thorn. >> Yeah, well, I mean, one of the areas we work in is trying to identify children who are being sold online in the US. A lot of people, first of all, think that's happening somewhere else. No, that's here in this country. A lot of these kids are coming out of foster care, or are runaways, and they get convinced by a pimp or a trafficker to be sold into prostitution, basically. So, we have 150,000 escort ads posted every single day in this country, and somewhere in there are children, and it's really difficult to look through that with your eye, and determine what's a child. So, we built a tool called Spotlight that basically reads and analyzes every ad as it comes in, and we layer on smart algorithms to say to an officer, "Hey, this is an ad you need to pay attention to. "It looks like this could be a child." And we've had over 6,000 children identified over the last year. >> John: That's amazing. >> You know, it happens in a situation where, you know, you have online it says, you know, this girl's 18, and it's actually a 15-year-old girl who met a man who said he was 17, he was actually 30, had already been convicted of sex trafficking, and within 48 hours of meeting this girl, he had her up online for sale. So, that sounds like a unique incident. It is not unique, it happens every single day in almost every city and town across this country. And the work we're doing is to find those kids faster, and stop that trauma. >> Well, I just wanna say congratulations. That's great work. We had a CUBE alumni, founder of CloudAir, Jeff Hammerbacher, good friend of theCUBE. He had a famous quote that he said on theCUBE, then said on the Charlie Rose Show, "The best minds of our generations "are thinking about how to make people click ads. "That sucks." This is an example where you can really put the best minds on some of the real important things. >> Yeah, we love Jeff. I read that quote all the time. >> It's really a most important quote. Well, thanks so much. Congratulations, great inspiration, great story. Bob, thanks for coming on, appreciate it. CUBE live coverage here at AWS re:Invent 2017, kicking off day one of three days of wall-to-wall coverage here, live in Las Vegas. We'll be right back with more after this short break.