>> 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)

>>Live from the Mandalay convention center in Las Vegas, Nevada it's doc cube at IBM insight, 2014. Here are your hosts, John furrier and Dave Volante. >>Okay. Welcome back everyone. We are here. Live in Las Vegas for IBM impact. This is the cube special presentation at IBM insight inside the digital experience. IBM insight go. Social media lounge. Uh, the social media gurus are here. John furry with David. Um, that's playing off the joke. We're just sharing on Twitter, but seriously, we're here. If I didn't see this on the noise, my coast, Dave latte, next guest Marsha Cola year. Who's the managing director of impact ingenuity at Marsha Marsha. Yes, that's your Twitter handle is awesome. Welcome. Welcome back. Welcome back. >>Well, thanks. It's thrilled to be here. >>So we were just joking about Halloween and we're going to be a social media guru. It's a little bit of a meme going around the internet. I mean, there is no social media guru. I mean, you can't really be a guru with developing technology. You can be a practitioner. I mean, I mean, guru, what is a social media? What is a social media guru? This, >>This is where, because I offered that. I would answer any question you ask me, you can ask me those things. Sure. Well, I think that's the problem. I think that's why it'd be a fabulous Halloween costume. I'm going to think about doing that one too, because people seem to be know to these folks. So following them to the ends of the earth, because of something that they sit on, social media, I mean that, that's a kind of a scary concept, but Google glass >>As well. I mean, I mean, I'm not going to go there. Um, but let's talk, let's go in into that, that theme. I mean, honestly, you know, Jeff Jonas was just on he's awesome. We always get in the weeds. He's a fun character to talk to, but he's super smart as we're on this G2 thing, observation space, but we're all internet of things, right? I mean, it reminds me of that book is to read to my kids thing one and thing two, you know, we, all things we're all in another thing. So what do you see as that impact to, uh, this digital transformation where not only are the humans connected to the machines, the data that they're exhausting or sharing or streaming, but the machines are connected and collecting as well. How is that going to change? What's your view on all this? >>While I have been in the technology sector, most of my, uh, most of my life, uh, and I appreciate and enjoy the technology. I never lose sight of the fact that this is about the people it's about us actually working together of actually learning together, doing whatever the hell it is we're needing to do. So if all of my appliances are actually then taking care of the mundane, if my water softener system is actually getting the water put in and getting delivered on the right day, you know, all, all the better. If the, if the toaster is alerting me to some sort of news, I'm thrilled. I love the idea of the technology. Actually being able to take care of all that stuff that we never wanted to do in the first place, but the technology has been so lousy over the last couple of years, actually forever, uh, that we've had to do this stuff because the technology isn't doing it for us. >>Sure. I was a patient out in the customer space because that's, you know, that's more of the home example, but even business now seems to be early innings. I mean, people are kicking the tires. You know, we've talked to all the gurus coming up here who are the tech side, IBM and customers. And the reality is we're all pro data, which we all kind of see that obvious social data and, you know, big data analytics, certainly helpful, but this transformation people are now really changing how to operate, operationalize their business with it. It's a huge daunting task and it's scary. Um, some people are like, whoa, I don't want to do it. Or, Hey, I'm jumping in. I'm cool. Is there a cool factor? Is there a scared factor? What's your, what's your observation from mountain talking to everyone out in the, in the marketplace? >>Well, first I would, I'll totally bash the, the idea that this is only a consumer play or that it doesn't apply to businesses. Think of all the, uh, the mundane and ridiculous things we have to do at work because they're not being taken care of us. We aren't taken care of for us by our desks. If you want to look at that way or our computers, I loved hearing about the, the new, uh, uh, pairing of, uh Wayblazer and, you know, Watson and the idea of the travel being taken care of us, what we discover because of the data that we're putting off each and every moment is their systems around us all the time that actually know our preferences, know how we would be handling this, but yet they don't do anything about it. So the idea that we can actually move forward in that way should be just as applicable to our business. Uh, a manager should not have to actually be asking some of the questions that they're asking the HR department is need to be asking how you're doing. It's evident by all the things that you put out into the world. And by just actually attending to what's going on, we have a huge opportunity to get back all that time that we've been wasting all these years. I'm just a stupid >>And just to what's. So what's the bottleneck is a fear security, oh, we don't want privacy. Marcia will get offended. If we tweet her, she knows that we know that she tweeted that. I mean, that's, that's a concern. People have, it seems to be, is it? Yeah. Well, look, go back up, >>But why is it a concern? It's because the people who've been doing it early are doing it horribly. I mean, they're doing it in not respectful ways. There isn't actually a real thought about how would I be okay with this doing? And then those are we're. So ahead of the curve, maybe because of the guru status, some of these social media, maybe that maybe that's the reason, >>Just look at the government, they were big data gurus and they screwed up that that whole Snowden thing was all like, Hey, just ask us, we'll give you our email addresses. You can search my email, have a nice day. >>It's a very different message. It's a very different conversation. It's a very different question. It's a very different level of respect that we have from one person working with another. I'm actually talking with people as opposed to at them. And instead of just making assumptions of actually participating, I mean, the idea that engagement is goal just implies that we haven't been engaged all these years. We haven't been thinking we haven't been doing, I haven't met. I personally, haven't met a really dumb person. It, you know, and years, and yet everything I do at would imply that we're, we're too stupid to be able to really think and act and, and be thoughtful about it. >>So you're an influencer. Um, you're out here in the digital sphere and you are, you're hearing influencer. Um, I mean, whatever you define it. Well, it's, I guess if they say so, if you are a VIP influencer, we'll go with that. Um, >>Digging on your Twitter stream here. Fantastic. >>Working on it. So share this law, you know, we'd love, we'd love to hear your stories cause you last year you were awesome with the cube. We'd love, love JV. Give us the update. What's going on with, sorry. We started together Ted at IBM conference. You super busy. Um, what's going on share with the folks out there. Some of the things you've been even into what your what's working show some, you know, some stuff that didn't work, what's going on, what's happening? What are you, what are you doing? What are you worried? All right, >>John, if you're going to ask them, I'm telling you you're really, if you're really ready, Don Damian, probably a little after I saw you last time after I was visiting here that, uh, our world's falling apart. And if all of us actually don't get on that. If we don't actually start figuring out how to use the precious time we have the, the precious money we have, the, the roles we have in our organizations, the resources at our disposal, our brains for good, not evil. I'm not so sure about the world that my son is going to be inheriting for example. And, uh, I'm, I'm at a point in my life where I realize, I, I know a heck of a lot in the world. I have a lot of skills, everybody. I know. I look at these people around me having tremendous skills. And instead of us just sort of churning out the butter one more year, uh, we best, we best be thinking about what can I do given what I have of my time and my resources, my skills, or whatever that is and apply that to what I have influence over and be able to make as much difference. >>Are we talking about God's last offer here, the sustainable world, or what's actually on all? >>Oh, you're not at the time that the timing is perfect too. If you think about it, don't seriously. >>What are we talking about? The deterioration of our planet? We're talking about social condition. Yes, >>I, well, I mean, I can go on and >>On about money return. I can, I can entertain for hours. You just made. The comment >>I made is that no matter where we look, that that scientists have pointed out that we're past the point of no return with our climate. We, uh, we look at the, uh, at the deterioration of the planet around us. I happen to live in the woods and I mean, deep in the woods and you can, you can see the change of how much rain is coming down. That didn't, I mean, I, I'm not, my intent here is not to talk about all the, that the problems around us. We all actually feel them, even if we're not acknowledging them, what I see is the wasted opportunity of us, not actually, re-examining what we're choosing to do and figure out how, whatever it is we're capable of doing could actually be helping instead of bringing it up. So how should people, let's say, people want to know that's good, but I just wanted to frame it. So let's >>Take people want to, so let's say that resonates to somebody in the audience. What should they do? How should they start pick a passion? And they >>Have, um, I mean, I, my, my approach to all the change work I do and have been doing with corporations for the last 20 years is actually not additive. It's not asking the question. What more could I do? Because that's usually what keeps people from doing it. I asked the question, what's keeping me from doing what I've always known needed to be done. So in, in our communities, you know, my experience is everybody knows who it is that could use some assistance, not in a handout sort of way in a reaching out and caring way of asking of, of having a conversation, a participating, and to be able to step back and ask that question. What's keeping me from doing that. We know what needs to be done, but we're not doing it. So how can I say, oh, well, what's keeping me from doing it. I don't have time to do it. Okay. Well, what can I do to actually just get a little bit more time to do something that matters in the world? So that that's the most, very, >>Very basic level. It could be slowly be that it's, >>It's less Twitter. It could also be a re-evaluating how much time I'm spending at work on stuff that could be automated. I mean, going back to this whole conversation about automation, it is to ask those questions. What I can do. That's just about time. Um, >>I, yeah, that is one of the biggest objections I don't have time. Right? >>Yeah. So what I find is when I talk about, uh, global health actually, is that when we look at the idea of health, not as in just exercising more or just eating, right, we're talking about fiscal health, we're talking about, uh, creating a world that is just, uh, a healthier place. When I ask people those questions, most of them can say, well, yeah, this isn't, this is important to me, but I don't know what to do about it. So one is, as you absolutely said, is finding, finding those passions and be able to figure out what you're going to do. But more importantly, to ask yourself that question, when am I going to do this? If not now, I feel like I'm, I'm falling. Like I, uh, I'm Mike is falling out. Let me, let me get that. >>Well, we chit chat a lot of hair. Yeah. Yeah. So I think, okay. So we're talking about different ways to find time. >>Um, Dave, I mean, I think it's a great time. I mean, the passionate thing, passionate thing is where the keyword is contributing, right? So like, I think it's a good time because I have, we, I, we both Dave and I both have four kids. So we see the new generation in their minds all the time because we're driving around, but they're impressionable right now is the old expression is you can grab the play though, and you can shape it. You can act, we can actually, as leaders and mature experience, instant people that have some skills in computing, we can influence like stem. We can influence women in tech. We can influence computer science curriculums or get influenced modern society because the new generation is coming in and they're natives, they're adopting and they're thirsty for leadership, but I don't think that they're seeing it. So I think there's really a good time. You've seen the Kickstarter crowdsourcing stuff is really becoming a part of this new tribe. So I believe the gravity around making things happen is participation, collaboration and data. Data is knowledge, endorsement, social proof. These are concepts that are easily transferable. If you can just, if you just wake up and do it. So I think, you know, >>If you just wake up and do it everywhere about, so Y Y if you wake up every day, why aren't you doing it today? >>We have Craig brown on earlier, he's doing $25,000 investments for kids to start companies, you know, whether the inner city kids. And that's pretty cool. I mean, so, you know, this is, this is the democratization piece, but in a connected network, it's frictionless communication. I mean, hell Twitter, overthrew governments. So you can have solidarity, peaceful solidarity as well as other rev revolution. So I think that's a very doable thing versus just checking the Basel. I volunteer to do something. And I think that has been more of like a peace Corps. I helped people. >>Uh, and I'm personally, I asked this question of everybody that I asked her, actually asked two questions of everybody I work with now. Uh, one of them is what can you not do? What can you not, not do actually. So if you, if you think to yourself, if I look back on my life, if I look back on my life, what is it that I thought to myself, oh, I didn't have time for that. Or I couldn't do it. You we've all heard that, you know, what do you want on your tombstone? However, that works. But I find that everybody, I know, think it has a burning need to be doing something useful in their lives. It's not just mission driven. It absolutely. It's a purpose. It's a connecting with, with connecting with people who are helping to move the world forward. And I just stopped. And I said, even in a business context, I say, you know, now it's time. We're kind of out of time. Get on with it, >>Please. The clock is ticking. Well, Jeff Jones was talking about the asteroid thing to geospatial smart geeky conversation. But the key thing out of that was better focus of finite resources. And that really comes down to the fundamental better decision-making. I mean, we, my wife says, so our kids will make better decisions. I mean, that's a mother talking to the kids, but that's our life now. So like, if we can make better decisions, that ultimately is the big data opportunity from social change to play to business. >>And then the second question absolutely, absolutely agree. Everything you said. I, the next big question I asked is what are you doing to improve the world? Now? I would say 50% of the people I say, just give me this completely deer in the headlights. Look, what do you mean to save the world or to improve the world, to change world? However you want to frame that. But I haven't met anybody in years that isn't interested in truly contributing, leaving the world a better place than they came into. And that's no matter what their, their demographic makeup is. That's no matter the community they live in, no matter what they're doing, people have a fundamental desire to do better. And so I asked that of every business person, every corporation I work with. And that's one of the things I love about this whole idea of, you know, building a smarter planet that should tie to every single thing we do. And, and when we lose sight of that, we see that, no, I think >>This is a really great conversation to have because it's, it's something that's emerging. And, you know, again, there's some obvious examples, oh, pebble watch crowdfunding. But if you look at really impactful things like open source software, you are seeing the playbook. I mean, the playbook is, you know, people can participate at any level. So the, the fear of getting this kind of group going is that I'm too busy or, you know, you can, the contribution doesn't have to be game changing for an individual could be one small piece of the puzzle. It could be small contribution. Someone might do more heavy lifting than the other. That's an open source concept. We've seen that work huge. A lot of leverage, a lot of participation. Um, so I think that's something that I really haven't seen get applied to at a large scale. I mean, you see the protest in Hong Kong are interesting. That's an indicator. What does that mean? Right. So what's your take on all? What do you think needs to happen to get more people tied into these shared missions? >>It's a little little over there off >>The ranch. A little bit more honesty. More honesty. Yeah. Yeah. I mean, not, not something that we talk about these sorts of events is that I I've gotten to the point where I do these large talks in front of thousands of people. And I ask everybody to turn to the person next to them and introduce themselves, honestly, like, why are you here? And why do you care? We've all gotten so wrapped up in the >>Who we are as well. And that's why I say, I love the idea of you being >>A social media guru for Halloween. It's just become, so it's so about the role that we've lost the connection with our humanity. And so I just, I asked people just to step back. So it's as simple. So yeah, I am all for the large initiatives. >>Yes. Self-aware is a really interesting concept. And that really what you're talking about here is, I mean, I make fun of myself. I put that out there. Probably gonna get some hate mail for that tweet, but no, it is what it is. I mean, I'm making fun of myself and us because we have to, because it's really not moving fast enough in the writer in my mind, at least I think, I mean, I think social media is a real, real game changer. I'm pro pro social media, but I mean, come on, if you can't make fun of yourself then, >>But what is social media do you mean? What is our untapped desire that why we're all participating in social media, where we've missed the opportunity for all these years to be human in everything that we're doing? Yeah. I mean, the idea that you can be, you know, wherever you are and be able to reach the people who have answers to be able to help you make better decisions is something that we've had that desire for a very long time. We've just been, not able to do that for so long that it's now it's time we get on >>With that. I would do the cube to Dave and I talk all the time. We want to broadcast out the data because I think people want to be part of something. And I think at the end of the day, it's human psychology is that being part of something makes psychology of the soul work better. It's like, okay, I want to be part of a group. I want to belong. It's a yearning, it's a tribe. Whatever that kind of collective group is, whether you know, the clown or the, or the guru or whatever, I think that's a people are yearning for that collectiveness of Griff groups. And I think the data gap is gravity. Like how do you a joke? It could be a serious conversation. It could be something provocative. I think content is a nice piece of gravity to kind of bring people together versus, you know, tweeting, Hey, look, how big I am. I got a zillion followers. >>Okay. So let's back up though. So content, so we can talk about the, the, the, the, the concept that has content. That's a lovely thing to do at a data conference, talking about the content it's about things we care about. That's what content is. So if we take that a step further and we actually extrapolate and say, how does this impact me? It's not because it's content it's because we're talking about topics that matter to each of us. And so the more we get back to that sort of conversation, the more we get back to that sort of point, I think we have a bigger opportunity to have conversations that matter and not be able to be. We are wasting our time doing the silly stuff. >>Okay. I'm getting the hook here, Marcia conversations that matter. That's really what it's all about. Changing the world. Thanks for calling the cube. Great to see you again. And, uh, we'll be right back after this short break live in Las Vegas date, you continues wall-to-wall coverage here, inside the cube, inside the digital experience in psycho with IBM social lounge. We right back after this short break,