>> Narrator: From around the globe, it's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Well, hello everybody and welcome again to theCUBE. We continue our initiative here at IBM Think and now we're joined by two distinguished guests who are really going the extra mile for us, I might say. Here we are in the States at a very reasonable hour, in Korea, it's a little later in the evening so we certainly appreciate their time and their patience here. We're joined by Mr. Khee-Hong Song, who is the CEO and President of IBM Korea and Mr. Jung Sik Suh, who is the CEO of Hyundai AutoEver, which is an IT service company affiliated with the Hyundai Motor Group. And gentlemen (greeting in Korean) Thank you for joining this. We appreciate it. >> Thank you. >> Thank you for inviting us. >> Hi. >> Yes, hi, very good to see you there. And I hope I didn't do the greeting injustice there. First off, Khee, I'll start with you. Let's talk about first off, kind of this digital transformation that transpires not only here in the United States, but of course is global. And certainly, with an IT advanced company like Korea, give us just really kind of a calibration, where are you in terms of this transformation in Korea with regard to digital? >> A lot of people are interested in the post-COVID world and how it is going to look like. What changes this pandemic will bring. The Korean government is really focusing on growing the digital sector. Taking this advantage, and taking this opportunity as a chance to really upgrade the entire IT system of the nation. So for example, like a Korean economy had been contracted by -1% and industry players also faced difficulties. For example, discount stores are -20% Y2Y. department stores are lost 30% of their revenue. But the government is injecting money to really change the game, leveraging the digital technology. >> Yeah, and you mentioned COVID, and obviously that's had a global impact. Not only in your operations here in the United States certainly, but Africa in Europe, and certainly in Asia as we talked about. Can you go just a little bit deeper on that in terms of what those impacts have been and maybe a little more specificity on coming out of that. You mentioned the economic impacts that Korea is currently suffering, but looking for a bounce back, looking for a rebound with the government. Maybe a little more specifics about the impact of COVID. And then Mr. Sung, I'll turn to you for that as well. First off, Khee, if you will. >> Okay, in an effort to recover from COVID-19 economic recession, Korean government announced Digital New Deal, which is to lay a foundation for digital economy that will spur economic growth and innovation. Now the policy aims to create a new digital economy, which is underpinned by new technologies such as 5G, big data and artificial intelligence. According to IDC research, 55% of Korean companies have already overcome the economic downturn and are moving toward the growth in next normal. They have been very active in making investments to become the enterprise of the future. And this is higher than global average of 37% in terms of recovery rate. This indicates that leading Korean companies are quickly preparing for the next, even in the face of a crisis. >> Jung, We've been hearing from Khee talking about the digital and certainly the impacts of COVID. And I assume that at Hyundai, you have had to deal with this certainly, this impact and are now coming out the other end, some very positive news from numbers we're hearing from Khee. If you could talk about though, maybe from your perspective in terms of that impact. And then, what kind of a rebound do you see or kind of positive uptick do you see in terms of digital in your business, say, in the next 12 to 18 months? >> I think the 12 to 18 months, we are reinforcing the digitalization, not just the working environment, but also others, especially for in terms of sales. Until now most of the B2C sales changed to digital or the internet environment, but unfortunately, car manufacturing OEM companies are not too ready for the e-commerce environment. But Hyundai is very actively, and proactively, and preemptively starting the e-commerce. So I think, next to 12 to 18 month, two-digit percent of our sales are will be fulfilled by internet-based. I mean, we'll have to face the most biggest and most challenging but possible change after COVID. >> Yeah, what's driving that then, is it just that people are more likely to want to be at home whether it's as a consumer or whether it's your workforce, whatever the case may be, but you're talking about this kind of going from a physical world to a more digital-based world as I'm hearing you describe it. Is that accurate? >> Yes. So we are the digital world, from just communicate with customer, but also our internal operation. Like the manufacturing environment and also the sales environment, et cetera. >> And Khee, if you would talk about maybe how this is impacting your business and just in terms of IBM in general. Not just with Hyundai, but I'm sure you support a lot of healthcare initiatives, a lot of other e-commerce initiatives and what have you, What's kind of the bottom line impact there for you right now in terms of this massive shift over to digital? >> Well, in IBM, our goal is to work with industry clients and technology partners to accelerate this transformation through automation, transition to hybrid cloud, and help our clients to really gain some benefits from their change. So one area I can talk about is automation. We see increasing requirements from our clients on automation for operational excellence, amid the economic downturn, and for hygiene purposes as well. So Seoul Asan Hospital is one of the leading hospitals in Korea and has the largest number of beds. Asan hospital and IBM worked together to develop a bed allocation automation system based on design thinking, workshop and garage method. The automation system considers a patient's specific preferences, surgery schedule, customized treatment for each patient, and various reservation status in each department. The result was outstanding. The hospital could reduce the bed assignment lead time from 20 minutes to seven minutes with a 0% error rate. And currently, more than a hundred hospitalization registration procedures are being processed every day without human intervention. And patient satisfaction and productivity of medical staff have improved significantly. That is just one great example of automation which is taking place in many other industries as well. Second is transformation to cloud. A large credit card company in Korea has chosen IBM as a partner to convert enterprise wide systems including the most complex account system to a managed private cloud using cloud technology from IBM and Red Hat. >> Khee, you talked about these key factors, if you will, about cloud transformation and different kinds of operational efficiencies and all these very fundamental. But very important factors to consider, when you're talking to your clients right now, what are their, I wouldn't say hesitations, but I guess maybe their challenges in deciding what tasks will go where and to what degree they're good with the cloud environment, to what degree they want it still on prem, to what, where the hybrid comes into play. I mean, these are all are fairly crucial decisions that your clients are making. >> Well, I think the barrier to any decision, like quick decision or sort of complete understanding is the technology itself is changing very quickly. I mean, last year, two years ago, versus now, when all technology companies, should we say something different. And that is not because it changed the position itself. The technology itself changed, and technology companies are responding to the trend. So that's why some clients get confused, and that confusion slows down the adaption of digital technology. But as I mentioned earlier, this pandemic situation, I'm pretty sure they're, like Mr. Sung can talk about some changes in Hyundai motors. Many companies realized that doing nothing or slowing down is not the best answer in this environment. And they are now proactively embracing those changes. >> So Jung, if you would then follow up on that, I would like to hear from you about Hyundai and the factors that you've considered in your digital decision making in terms of workloads, and capacities, and just where you house information, where you house your data, where you process it. What are some of those factors that you have thought about and then maybe going forward, how much more are you going to do? What are you considering right now in terms of future transformations? >> I think the other, our competitor, the other OEMs also think like that the car itself should be changed to digital. It means that, currently, the software portion of the car is just a seven to 10% of total our, the procurement. But it'll be changed to 20 to 30% in five years. It means that some portion will be to increased by three times There is a one our research changed. The other one is that kind of a software mostly located and not just in the car, which means that car is just a software edge activity. It means that just that the input and output, or some real-time transaction, or other computation and calculation analysis and decision could be the car cloud. Therefore, the cloud is main party of the car software. And also the car is it's just to edge. We have edge cloud and main cloud. It will be occurred just to within just several years. First, really, Hyundai has currently more than 40% of the car is connected in listening. And also cumulatively, we are connected by around the four million car in the word. It will be changed to 10 million car would be connected within one years. >> So 10 million Hyundai cars will be connected to cloud generating information and also- >> Yes, collecting information. And we are ready for the OTA, which means over-the-air software update for the 10 million car within one years. And also, it will double up year by year. >> Okay. >> Which means that all of the car, all the operated by cloud. >> Okay. >> And cars, it says to input and output an edge activities, therefore car is on cloud. >> Okay. >> John: Right? Khee: Interesting. >> Jung: That is the major driver for our digital transformation. >> And if you would, just what role is IBM having that? You're talking about a massive increase of 10 million cars is a very impressive number. >> And the data, the 10 million cars are producing are will be enormous. So IBM's role is actually helping clients in this kind of situation. To help those companies collect data and then like a seamless communication with the cloud. So that at the real time, the 10 million cars get the information timely. And also, like all those cars are communicating with each other that is made possible upon a hybrid cloud platform. And I think that is IBM's contribution to Hyundai Motors. Not just Hyundai Motors, but industries who have similar challenges and desires. >> One more thing, lately, IBM helped us our all IT operation in US and Europe, which composed of our 50% of our revenue come from. Therefore it means that dozens of billion of revenue operation is located in US and Europe. All over the US, Europe IT operation conducted by the IBM India and orchestrated by IBM Korean people. >> So it's amazing as Mr. Suh mentioned, IBM Korea is leading the project. All the service delivery is done in India leveraging IBM India. And we are serving Hyundai motors in the United States and Europe. So it's a truly a global IT operation environment. And that is made possible based upon IBM's cloud technology. >> Well, your summary was spot on. I couldn't say it any better, Khee. Thank you for that. Jung, thank you as well. Talking about this impressive global impact and really partnership that Hyundai is taking with IBM in the several continents. And making it work for millions of consumers around the world. Thank you both for your time today. I appreciate it. >> Khee: Thank you very much, John. >> Jung: Thank you. >> All right, we've been talking about Korea as an IT power country for the IBM perspective. And certainly, using Hyundai is a beautiful example of just how this partnership is working and growing, and providing great service for consumers at the end of the day. You've been watching "theCube" and IBM Think. (upbeat theme music) (upbeat theme music) (humming)

(bright theme music) (humming) >> From around the globe, it's "theCUBE" with digital coverage of IBM Think 2021 brought to you by IBM. >> Well, hello everybody and welcome again to "theCUBE." We'll continue our initiative here at IBM Think and now we're joined by two distinguished guests who are really going the extra mile for us, I might say. Here we are in the States at a very reasonable hour, in Korea, it's a little later in the evening so we certainly appreciate their time and their patience here. We're joined by Mr. Ki-Hong Song, who is the CEO and President of IBM Korea and Mr. Jung Sik Suh, who is the CEO of Hyundai AutoEver, which is an IT service company affiliated with the Hyundai Motor Group. And gentlemen (speaking foreign language) Thank you for joining this. We appreciate it. >> Thank you. >> Thank you for inviting us. >> Hi. >> Yes, hi, very good to see you there. And I hope I didn't do the greeting injustice there. First off, Ki, I'll start with you. Let's talk about first off, kind of this digital transformation that transpires not only here in the United States, but of course is global. And certainly, with an IT advanced company like Korea, give us just really kind of a calibration, where are you in terms of this transformation in Korea with regard to digital? >> A lot of people are interested in the post-COVID world and how it is going to look like. What changes this pandemic will bring. The Korean government is really focusing on growing the digital sector. Taking this advantage, and taking this opportunity as a chance to really upgrade the entire IT system of the nation. So for example, like a Korean economy had been contracted by -1% and industry players also faced difficulties. For example, discount stores are -20% Y2Y. department stores are lost 30% of their revenue. But the government is injecting money to really change the game, leveraging the digital technology. >> Yeah, and you mentioned COVID, and obviously that's had a global impact. Not only in your operations here in the United States certainly, but Africa in Europe, and certainly in Asia as we talked about. Can you go just a little bit deeper on that in terms of what those impacts have been and maybe a little more specificity on coming out of that. You mentioned the economic impacts that Korea is currently suffering, but looking for a bounce back, looking for a rebound with the government. Maybe a little more specifics about the impact of COVID. And then Mr. Sung, I'll turn to you for that as well. First off, Ki, if you will. >> Okay, in an effort to recover from COVID-19 economic recession, Korean government announced Digital New Deal, which is to lay a foundation for digital economy that will spur economic growth and innovation. Now the policy aims to create a new digital economy, which is underpinned by new technologies such as 5G, big data and artificial intelligence. According to IDC research, 55% of Korean companies have already overcome the economic downturn and are moving toward the growth in next normal. They have been very active in making investments to become the enterprise of the future. And this is higher than global average of 37% in terms of recovery rate. This indicates that leading Korean companies are quickly preparing for the next, even in the face of a crisis. >> Jung, We've been hearing from Ki talking about the digital and certainly the impacts of COVID. And I assume that at Hyundai, you have had to deal with this certainly, this impact and are now coming out the other end, some very positive news from numbers we're hearing from Ki. If you could talk about though, maybe from your perspective in terms of that impact. And then, what kind of a rebound do you see or kind of positive uptick do you see in terms of digital in your business, say, in the next 12 to 18 months? >> I think in this 12 to 18 months, we are reinforce the digitalization, not just the working environment, but also others take this, especially for in terms of sales. Until now most of the B2C sales changed to digital or the internet environment, but unfortunately, car manufacturing OEM companies are not too ready for the e-commerce environment. But Hyundai is very actively, and proactively, and preemptively started the e-commerce. So I think, next to 12 to 18 month, two-digit percent of our sales are will be fulfilled by internet-based. I mean, we'll have to face the most biggest and most challenging but possible change after COVID. >> Yeah, what's driving that then, is it just that people are more likely to want to be at home whether it's as a consumer or whether it's your workforce, whatever the case may be, but you're talking about this kind of going from a physical world to a more digital-based world as I'm hearing you describe it. Is that accurate? >> Yes. So we are the digital world, from just communicate with customer, but also our internal operation. Like the manufacturing environment and also the sales environment, et cetera. >> And Ki, if you would talk about maybe how this is impacting your business and just in terms of IBM in general. Not just with Hyundai, but I'm sure you support a lot of healthcare initiatives, a lot of other e-commerce initiatives and what have you, What's kind of the bottom line impact there for you right now in terms of this massive shift over to digital? >> We'll, in IBM, our goal is to work with industry clients and technology partners to accelerate this transformation through automation, transition to hybrid cloud, and help our clients to really gain some benefits from their change. So one area I can talk about is automation. We see increasing requirements from our clients on automation for operational excellence, Meet the economic downturn, and for hygiene purposes as well. So Seoul Asan Hospital is one of the leading hospitals in Korea and has the largest number of beds. Asan hospital and IBM worked together to develop a better allocation automation system based on design thinking, workshop and garage method. The automation system considers a patient's specific preferences, surgery schedule, customized treatment for each patient, and various reservation status in each department. The result was outstanding. The hospital could reduce the bed assignment lead time from 20 minutes to seven minutes with a 0% error rate. And currently, more than hundred hospitalization registration procedures are being processed every day without human intervention. And patient satisfaction and productivity of medical staff have improved significantly. That is just one great example of automation which is taking place in many other industries as well. Second is transformation to cloud. A large credit card company in Korea has chosen IBM as a partner to convert enterprise wide systems including the most complex account system to a managed private cloud using cloud technology from IBM and Red Hat. >> Ki, you talked about these key factors, if you will, about cloud transformation and different kinds of operational efficiencies and all these very fundamental. But very important factors to consider, when you're talking to your clients right now, what are their, I wouldn't say hesitations, but I guess maybe their challenges in deciding what tasks will go where and to what degree they're good with the cloud environment, to what degree they want it still on prem, to what, where the hybrid comes into play. I mean, these are all are fairly crucial decisions that your clients are making. >> Well, I think the barrier to any decision, like quick decision or sort of complete understanding is the technology itself is changing very quickly. I mean, last year, two years ago, versus now, when all technology companies, should we say something different. And that is not because it changed the position itself. The technology itself changed, and technology companies are responding to the trend. So that's why some clients get confused, and that confusion slows down the adaption of digital technology. But as I mentioned earlier, this pandemic situation, I'm pretty sure they're, like Mr. Sung can talk about some changes in Hyundai motors. Many companies realized that doing nothing or slowing down is not the best answer in this environment. And they are now proactively embracing those changes. >> So Jung, if you would then follow up on that, I would like to hear from you about Hyundai and the factors that you've considered in your digital decision making in terms of workloads, and capacities, and just where you house information, where you house your data, where you process it. What are some of those factors that you have thought about and then maybe going forward, how much more are you going to do? What are you considering right now in terms of future transformations? >> I think the other, our competitor, the other OEMs also think like that the car itself should be changed to digital. It means that, currently, the software portion of the car is just a seven to 10% of total our, the procurement. But it'll be changed to 20 to 30% in five years. It means that some portion will be to increased by three times There is a one our research changed. The other one is that kind of a software mostly located and not just in the car, which means that car is just a software edge activity. It means that just that the input and output, or some real-time transaction, or other computation and calculation analysis and decision could be the car cloud. Therefore, the cloud is main party of the car software. And also the car is it's just to edge. We have edge cloud and main cloud. It will be occurred just to within just several years. First, really, Hyundai has currently more than 40% of the car is connected in listening. And also cumulatively, we are connected by around the four million car in the word. It will be changed to 10 million car would be connected within one years. >> So 10 million Hyundai cars will be connected to cloud generating information and also- >> Yes, collecting information. And we are ready for the OTA, which means over-the-air software update for the 10 million car within one years. And also, it will double up year by year. >> Okay. >> Which means that all of the car, all the operated by cloud. >> Okay. >> And cars, it says to input and output an edge activities, therefore car is on cloud. >> Okay. >> Right? >> Interesting. >> That is the major driver for our digital transformation. >> And if you would, just what role is IBM having that? You're talking about a massive increase of 10 million cars is a very impressive number. >> And the data, the 10 million cars are producing are will be enormous. So IBM's role is actually helping clients in this kind of situation. To help those companies collect data and then like a seamless communication with the cloud. So that at the real time, the 10 million cars get the information timely. And also, like all those cars are communicating with each other that is made possible upon a hybrid cloud platform. And I think that is IBM's contribution to Hyundai Motors. Not just Hyundai Motors, but industries who have similar challenges and desires. >> One more thing, lately, IBM helped us our all IT operation in US and Europe, which composed of our 50% of our revenue come from. Therefore it means that dozens of billion of revenue operation is located in US and Europe. All over the US, Europe IT operation conducted by the IBM India and orchestrated by IBM Korean people. >> So it's amazing as Mr. Suh mentioned, IBM Korea is leading the project. All the service delivery is done in India leveraging IBM India. And we are serving Hyundai motors in the United States and Europe. So it's a truly a global IT operation environment. And that is made possible based upon IBM's cloud technology. >> Well, your summary was spot on. I couldn't say it any better, Ki. Thank you for that. Jung, thank you as well. Talking about this impressive global impact and really partnership that Hyundai is taking with IBM in the several continents. And making it work for millions of consumers around the world. Thank you both for your time today. I appreciate it. >> Thank you very much, John. >> Thank you. >> All right, we've been talking about Korea as an IT power country for the IBM perspective. And certainly, using Hyundai is a beautiful example of just how this partnership is working and growing, and providing great service for consumers at the end of the day. You've been watching "theCube" and IBM Think. (upbeat theme music) (upbeat theme music) (humming)

(upbeat music) >> From around the globe, it's theCUBE! With digital coverage of IBM Think 2021 brought to you by IBM. >> Well, hello everybody. and welcome again to theCUBE. We continue our initiative here of IBM Think. and now we're joined by two distinguished guests who are really going the extra mile for us, I might say. Here we are in the States at a very reasonable hour, in Korea, it's a little later in the evening so we certainly appreciate their time and their patience here. We're joined by Mr. Kheehong Song, who is the CEO and president of IBM Korea and Mr. Jung-Sik Suh, who is the CEO of Hyundai AutoEver which is an IT service company affiliated with the Hyundai Motor Group. Gentlemen, (speaks in foreign language) thank you for joining us. We appreciate it. >> Thank you. >> Thank you, hi. >> Hi, it's very good to see you there. And I hope I didn't do the greeting injustice there. First off, Khee I'll start with you. Let's talk about first off, kind of this digital transformation that transpires not only here in the United States, but of course, is global. And certainly with an IT advanced company like Korea, give us just really kind of a calibration, where are you in terms of this transformation in Korea with regard to digital? >> A lot of people are interested in the post COVID world and how it is going to look like, what changes this pandemic will bring. The Korean government is really focusing on growing the digital sector, taking this advantage. And taking this opportunity here as a chance to really upgrade the entire IT system of the nation. So for example, like a Korean economy had been contracted by negative 1%, and industry players also faced difficulties. For example, discount stores, negative 20% Y2Y department stores lost 30% of their revenue, but the government is injecting money to really change the game, leveraging the digital technology. >> Yeah, and you mentioned COVID. And obviously that's had a global impact, you know, not only in your operations here in the United States, certainly, but Africa, in Europe and certainly in Asia as we talked about. Can you go just a little bit deeper on that in terms of what those impacts have been, and maybe a little more specificity on coming out of that? You mentioned the economic impacts that Korea is currently suffering, but looking for a bounce back, looking for a rebound with the government, maybe a little more specifics about the impact of COVID. And then Mr. Song, I'm going to turn to you for that as well. First off, Khee, if you would. >> Okay. In an effort to recover from COVID-19 economic recession, Korean government announced digital new deal which is to lay a foundation for a digital economy that will spur economic growth and innovation. Now, the policy aims to create a new digital economy which is underpinned by new technologies, such as 5G, big data and artificial intelligence. According to IDC research, 55% of Korean companies have already overcome the economic downturn and are moving toward across the next normal. They have been very active in making investments to become the enterprise of the future. And this is higher than global average of 37%, in terms of recovery rate. This indicates that leading Korean companies are quickly preparing for the next even in the face of a crisis. >> Jung, we've been hearing from Khee talking about the digital and certainly the impacts of COVID. And I've assumed that at Hyundai, you know, you have had to deal with this, certainly this impact, and are not coming out the other end some very positive news from numbers we're hearing from Khee. If you could talk about though, maybe what from your perspective, in terms of that impact and then what kind of a rebound do you see, or kind of positive uptake do you see in terms of digital and your business say in the next 12 to 18 months? >> I think the next 12 to 18 months, the reinforcers of digitalization, not just the working environment, but also other respect especially for the... in terms of sales. You know, until now, most of the B2C Series changed to digital or the internet environment, but unfortunately, car manufacturing OEM companies aren't ready for the E-commerce environment. But Hyundai is very actively and proactively, and preemptively started at E-commerce. So I think next 12 to 18 month, two digit percent of our sales, I mean fulfilled by internet (mumbles), I mean the objective is the most biggest and most challenging, but possible changing after COVID. >> Yeah, what's driving that and then, it's just that people are more likely to want to be at home whether it's as a consumer or whether it's your workforce whatever the case may be, but you're talking about this kind of going from a physical world to a more digital-based world, as I'm hearing you describe that, is that accurate? >> Yes. So we are, the digital world, from just communicate with the customer, but also the, our internal operation, you know, like the manufacturing environment, and also the sales environment, et cetera. >> And Khee, if you would talk about maybe how this is impacting your business and just in terms of IBM in general, not just with Hyundai, but I'm sure you support a lot of healthcare initiatives, a lot of other E-commerce initiatives and what have you. What's kind of the bottom line impact there for you right now, in terms of this massive shift over to digital? >> In IBM, our goal is to work with industry clients and technology partners to accelerate these trends maybe mention through automation, transition to hybrid cloud and help our clients to really gain some benefits from their change. So one area I can talk about is automation. We see increasing requirements from our clients on automation for operational excellence, meet the economic downturn, and for hygiene purposes as well. So Seoul Asan hospital is one of the leading hospitals in Korea and has the largest number of beds. Asan hospital and IBM worked together to develop a bed location automation system, based on design thinking workshop and garage method. The automation system considers our patient's specific preferences, surgery schedule, customized treatment for each patient, and various reservation status in each department. The result was outstanding. The hospital could reduce the bed assignment lead time from 20 minutes to seven minute with a 0% error rate. And currently more than a hundred hospitalization registration procedures are being processed every day without human intervention. And patient satisfaction and productivity of medical staff have improved significantly. That is just one great example of automation which is taking place in many other industries as well. Second is a transformation to cloud. A large credit card company in Korea has chosen IBM as a partner to convert enterprise wide systems including the most complex account system to manage it private cloud using cloud technology from IBM and Red Hat. >> Khee, you talk about these key factors, if you will, about cloud transformation and different kinds of operational efficiencies, and all these you very fundamental but very important factors to consider. When you're talking to your clients right now, what are their I wouldn't say hesitations, but I guess maybe their challenges in deciding what tasks will go where, and to what degree they're good with the cloud environment, to what degree they want it still on prem, to what where the hybrid comes into play. I mean, these are all are fairly crucial decisions that your clients are making. >> I think the barrier to any decision, like a quick decision or sort of complete understanding is the technology itself is changing very quickly. I mean last year, two years ago versus now when all technology companies should say something different. And that is not because they changed the position. Itself, the technology itself changed and technology companies are responding to that trend. So that's why some clients get confused, and that confusion slows down the adoption of digital technology. But as I mentioned earlier, this pandemic situation, I'm pretty sure they're like Mr. Suh can talk about some changes in Hyundai motors. Many companies realize that doing nothing or slowing down is not the best answer in this environment. And they are now proactively embracing those changes. >> So Jun, if you would then follow up on that, I would like to hear from you about Hyundai, and the factors that you've considered in your digital decision-making, in terms of workloads and capacities, and you know, just where you house information, where you house your data, where you process it. What are some of those factors that you have thought about and then maybe going forward how much more are you going to do? What else do, what are you considering right now in terms of future transformations? >> I think the other well, competitor the other OEMs also think like that, the, you know, the car itself should be changed to digital. It means that, you know currently the software portion of the car is just seven to 10% of total our, the procurement, but it'll be change it to 20 to 30% in near to five years. It means that software portion will be increased by three times. That is one our, that is to change it. The other one is that kind of a software mostly located not just in the car, which means that car is just a software engine activity. It means that just that the input and output, or some real time trajection. All other computation and calculation analysis and decision could be the car cloud. Therefore, the cloud is main body of the car software. And also just car it's just to edge. We have edge cloud and main cloud. It will be occurred just within several years. Because first of all, firstly, Hyundai has currently more than 40% of the car is connected in listening. And also cumulatively, we are connected by around four million car in the world. It will be change to 10 million, car would be connected within one years. >> So 10 million Hyundai cars will be connected to cloud generating information? >> Yes, collecting information, and we are ready for the OTA, which means that all over the air, software update for the 10 million car within one years. And also it will be double up, double up, double, year by year. >> Okay. >> Which means that all of the car will be operated by cloud. >> Okay. >> And car is test to input and output, and activities. Therefore car is on cloud. >> Okay. >> Right? >> Interesting. >> That is the major driver for our district transformation. >> And if you would just, what role is IBM have in that? You're talking about a massive increase of 10 million cars is a very impressive number. >> And the data, the 10 million cars are producing will be enormous. So IBM's role is actually helping clients in this kind of situation. To help those companies collect data and then like a seamless communication with the cloud. So they're like at the real time, the 10 million cars get the information timely, and also like all those cars are communicating with each other, that is made possible upon a hybrid cloud platform. And I think that is IBM's contribution to Hyundai Motors, not just Hyundai Motors, but industries who have similar challenges and desires. >> One more thing, already, IBM helped us, our IT operation in US and Europe, which composed of our 50% of our revenue come from. Therefore it means that (mumbles) billion revenue operation is located in US and Europe. All over the US, Europe, IT operation conducted by the IBM India. And orchestrated by IBM Korean people. >> So it's amazing as Mr. Suh mentioned like IBM Korea is leading the project. All the service delivery is done in India, leveraging IBM India. And we are serving Hyundai Motors in the United States and Europe. So it's truly a global IT operation environment, and that is made possible based upon IBM's cloud technology. >> Well, your summary was spot on. I couldn't say that any better. Khee, thank you for that. Jun, thank you as well, talking about this impressive global impact and really partnership that Hyundai is taking with IBM and the several continents. And making it work for millions of consumers around the world. Thank you both for your time today. I appreciate it. >> Thank you. >> Thank you very much, John. >> Thank you. >> All right, we've been talking about Korea as an IT powered country for the IBM perspective. And certainly using Hyundai is a beautiful example of just how this partnership is working and growing and providing great service for consumers, at the end of the day. You've been watching theCUBE and IBM Think. (upbeat music)

(upbeat pop music) >> From our studios in the heart of Silicon Valley, Palo Alto, California, this is a CubeConversation. >> Hello, everyone welcome to this CUBE Conversation here in Palo Alto, California, I'm John Furrier, co-host of theCUBE. We are here forth Inhi Cho Suh General Manager of IBM Watson, Customer Engagement, Former Cube alumni, I think she's been on dozens of times. Great to see you again. Welcome to our Palo Alto Studios. >> Yeah, great being here, John. >> So, we haven't chatted in awhile. IBM thing just happened, a little bit of a rainy event, here in February. Interesting change over since we last talked, but first give an update on what you're up to these days, what group are you leading, what's new? >> Okay, well first of all, I'm here based in California, which I'm excited about, and I lead our Watson West office, which is our Watson headquarters, here on the west coast, in downtown San Francisco, and we hosted our Think Conference, and at Think I lead with, in IBM, what we call our Watson Customer Engagement Business Unit, which is really the business applications, of how we apply Watson and other disruptive tech to a line of business audiences, both SAS and on premise software, so really excited about the areas of applying AI and machine learning as well as Blockchain to things like supply chain, and logistics, to order management, to next generation of retail. A lot of new, exciting areas. >> Yeah, we've had many conversations over the years from big data to as your career spanned across IBM, and you have a much more horizontal view of things, now. You're horizontally scalable, as we say in the cloud world. What's your observation of the trends these days? Because there's a lot waves. Actually, the waves that you guys announced, was the IBM, Watson NE ware and the cloud private ware. Marvin and I had an amazing conversation that video went viral. This is now getting a big tailwind for IBM. What's your thoughts in general about the overall ecosystem, because you're here in Silicon Valley, you've seen the big waves, you've got another big data world, cloud is here, multi cloud. What's your thoughts on the big mega-trends? >> Yeah, that's a good question. I think the first chapter of cloud, everyone ran to public cloud. When you look at it through the lens of enterprise, though, the hot topic right now in the second chapter is really about not just public cloud, but multi-cloud, hybrid cloud. Meaning, whether it's a private, public, it's about thinking about the applications and the nature of the applications and regardless of where the data sits, what are the implications of actually getting work done? Through, kind of, new container services, new ways of microservices in the development, of how APIs are integrated, and so, the hot topic right now is definitely hybrid cloud, multi cloud. And the work we've done to certify, what we call, IBM cloud private really enables us to not just take any business application to any cloud in our cloud, as well, but actually to enable Watson and Watson based applications also across multi cloud environments. >> So, chapter two, Jenny mentioned that in her key notes, I want to dig into that because we've been talking a lot about multi cloud architecture, and one of the big debates has been, in the industry, oh, don't pick a soul cloud. I've been writing a bunch of content about that at this DOD jedi deal with Amazon and Oracle, fighting for it out there, but that's also happening at the enterprise, but the reality is, everyone has multiple clouds. If you've got a sales force or if you've got this and that and the other thing, you probably have multiple clouds, so it's not so much soul cloud vs. as it is, workloads having a cloud for the right job and that seems to be validated at IBM Think, in talking to the top technical people and in the industry. They all say, pick the right cloud for the job. And we've heard that before in Big Data. Pick the right tool for the job. So, given that, workloads seem to be driving the demand for cloud. Since you're on the app side, how are you seeing that? Because the world's flipped. It used to be infrastructure and software enable the app's capabilities. Now the workloads have infrastructure as code, made with cloud, they're driving the requirements. This is a change over. >> It is a big change and part of, I would say, when people first ran to the cloud, and a lot of the public cloud services were digital SaaS services, where people were wanting to stitch multiple applications across clouds, and that became a challenge, so in this next iteration, that I'm seeing is, really, a couple things. One is, data gravity. So, where does the data actually reside, for the workload that's actually happening? Whether it's the transactions, whether it's customer information, whether it's product information, that's one piece. The second piece is a lot more analytics, right? And the spectrum of analytics running from traditional warehouse capabilities, to more, let's say, larger scale big data projects to full blown advanced algorithms and AI applications, is, people are saying, look, not only do I want to stitch these applications across multiple clouds; I also want to make sure I can actually tap into the data to apply new types of analytics and derive new services and new values out of relationships, understanding of how products are consumed, and so forth. So, for us, when we think about it is, we want to be able to enable that fluid understanding of data across the clouds, as well as protect and be thoughtful about the data privacy rights around it, compliance around GDPR, as well as how we think about the security aspects as well, for the enterprise. >> That is a great point. I think I want to drill down on the data piece, your background on data obviously is going to be key in your job now obviously, it's pretty obvious with Watson, but David Floyd, a wiki bonds research analyst, just posted a taxonomy of hybrid cloud research report that laid out the different kinds of cloud you could have. There's edge clouds, there's all kinds of things from public to edge, so when you look at that, you're thinking, okay, the data plain is the critical nature of the cloud. Now, depending on which cloud architecture for the use case, the workload, whatever, the data plain seems to be this magical opportunity. AI is going to have a big part of that. Can you just talk about how you guys see that evolving? Because, obviously, AI is a killer part of your strategy. This data piece is inter-operating across the clouds. >> Yes. >> Data management governs you're smiling, cause there's a killer answer coming. >> Totally. This is such a great set up. Actually, Ginni even said it in her keynote at Think, which was, you can't have an AI strategy without an information architecture strategy, which is an IA strategy, and information architecture is all about what you said: it's data preparation; understanding the foundation of it, making sure you've got the right governance structure, the integration of it, and then actually how you apply the more advanced analytics on top. So, information architecture and thinking about the data aspects in all kinds of data. Majority of the data actually sits behind, what I would say, the traditional public firewall. So, it sits behind the firewalls of our enterprise clients, like 80 plus percent of it, and then, many of the clients, we actually recently did a study, with about 5,000 senior executives, across many, many thousands of organizations, and 85% of them want to apply AI to improve their customer service, to improve the way they engage their clients and their products and services, so this is a huge opportunity right now for pretty much every organization to think through; kind of their data strategy. Their information architecture strategy, as part of their overall AI strategy. >> So, a question a got on twitter comes up a lot, and, also on my notes here, I wanted to ask you is, how can companies increase transparency trust and mitigate bias in AI? Because this comes up a lot and that's the questions that come in from the community is, Hey, I got my site, my apps running in Germany. I've got users over there, I'm global. I have to manage compliance, I got all this governess now, I'm over my shoulders, kind of a pain in the butt, but also I don't want to have the software be skewed on bias and other things, and then, I also get this whole Facebook dynamic going on, where it's like, I don't trust people holding my data. This is a big, huge issue. >> It is enormous. >> You guys are in the middle of it, what's your thoughts, what's the update, what's the dynamic and what's the solution? >> So, this is a big topic. I think we could do a whole episode just on this topic alone. So, trust and developing trust and transparency in AI should be a fundamental requirement across many, many different types of institutions. So, first of all, the responsibility doesn't sit only with the technology vendors; it's a shared responsibility across government institutions, the consumers, as well as the business leaders, in terms of how they're thinking about it. The more important piece, though, is when you think about the population that's available, that really understands AI, and they're actually coding and developing on it, is that we have to think about the diverse population that's participating in the governance of it, because you don't want just one tribe or one group that's coding and developing the algorithms, or deciding the decision models. >> Like the nerds or the geeks; they're a social aspect, society aspect as well, right? Social science. >> Exactly. I actually just did a recent conversational series with Northwestern Kellogg's business school, around the importance of developing trust and transparency, not only in the algorithms themselves, but the methodology of how you think about culture and value and ethics come into play through different lens, depending on the country you live in, as you kind of referenced, depending on your different values and religious backgrounds. It may because of different institutional and/or policy positions, depending on the nature, and so there has to be a general awareness of this that's thoughtful. Now, why I'm so excited about the work we're doing at IBM is we've actually launched a couple new initiatives. One is, what we call, AI OpenScale, which is really a platform and an opportunity to have the ability to begin to apply AI, see how AI operations and models function in production. We have methodologies in terms of engaging understanding fairness, so there's a 360 degree fairness kit, which is actually available in the open source world, there's a set of tools to understand and train people on recognizing bias, so even just definitions of, what do you mean by bias? It could be things like, group think, it could be, you're just self selecting on certain data sets to reinforce your hypotheses, it could be unconscious levels and it's not just traditionally socially oriented, types of bias. >> It could be data bias, too. It could be data bias, right? >> Totally. Machine generated biases in IOT world, also. >> So, contextual and behavioral biases kind of kick into play here. >> Yeah, but it starts with transparency trust. It also starts with thoughtful governance, it starts with understanding in your position on policy around data privacy, and those things are things that should be educational conversations across the entire industry. >> How far along are we on the progress bar there? I mean, it seems like it's early and we seem to be talking for awhile, but it seems even more early than most people think. Still a lot more work. Your thoughts on where the progress bar is on this whole mash up of tech and social issues around bias and data? Where are we? >> We're really at the early stages, and part of the reason we're at the early stages is I think people have, so far, really applied AI in very simple task oriented applications. The more, what we call, broad AI, meaning multi task work flow applications are starting, and we're also starting seeing in the enterprise. Now, in the enterprise world, you can still have bias, so, for example, when you talked about data bias, one of the simple examples I use is, think about loan approvals. If one of the criteria may be based on gender, you may have a sensitivity around the lack of women owned business leaders, and that could be a scoring algorithm that says, hey, maybe it's a higher risk when in fact, it's not necessarily a higher risk, it's just that the sampling is off, right. So, that would be a detection to say, hey maybe you have sensitivity around that data set, because you actually have an insufficient amount of data. So, part of data detection and understanding biases; where you have sampling of data that's incorrect, where your segmentation could be rethought, where it may just require an additional supervision or like decision making criteria as part of your governance process. >> This is actually a great area for young people to get involved, whether at their universities or curriculum, this kind of seems to be, whether it's political science and/or data science kind of coming together, you kind of have a mash. What's your advice to people watching that might be either in high school, college, or rethinking their career, because this seems to be hot area. >> It is a hot area. I would recommend it for every student at every age, quite frankly and we're at such an early stage that it's not too late to join and you're not too young nor are you too old to actually get in the industry, so that's point one. This is a great time for everyone to get involved. The second piece is, I would just start with online courses that are available, as well as participate in communities and companies like IBM, where we actually make available on a number of our web based applications, that you can actually do some online training and courses to understand the services that we have, to begin to understand the taxonomy and the language, so a very simple set, would be like, learn the language of AI first, and then, as you're learning coding, if you're more technically inclined, there's just a myriad of classes available. >> Final question, before I move on to the topic around inclusion and diversity, machine learning is impacting all verticals. I was just in an interview, talking with Don En-ju-bin-ski, she's got a company where it's neuroscience and machine learning coming together. Machine learning's being impacted all over. We mentioned basic data bias, and machine learning can help there. Machine learning meets blank every vertical, every market, is being impacted machine learning, which will trigger some of the things you're seeing on the app side. Your thoughts, looking at where you've come from in your career at IBM to now, just the evolution of what machine learning has enabled, your thoughts on the impact of machine learning. >> Oh, it's exciting and I'll give you a real simple example, so one of the great things my own team actually did was apply machine learning to, everyone loves the holiday shopping period, right? Between Thanksgiving to New Years, so we actually develop, what we call, Watson Order Optimizer and one of my favorite brands is REI, so the recreational equipment incorporated company, they actually applied our Watson Order Optimizer to optimize in real time. The best place, let's say you want to order a kayak or a T-shirt or a hiking boot, but the best way to create the algorithms to ship from different stores, and shipping from stores, for most retailers, is a high cost variable, because you don't know what the inventory positions are, you don't necessarily know the movement of traffic into that store, you may not even know what the price promotions are, so what was exciting about putting machine learning algorithms to this was, we could actually curate things like shipping and tax information, inventory positions of products in stores, pricing, a movement of goods as part of that calculation. So, this is like a set of business rules that are automatically developed, using Watson, in a way that would be almost impossible for any human to actually come up with all of the possible business roles, right? Because this is such a complex situation, and then you're trying to do it at the peak time, which is, like Black Friday, Cyber Monday Weekend, so we were able to actually apply Watson Machine Learning to create the business roles for when it should be shipped from a warehouse or a particular store. In order to meet the customer requirement, which is the fulfillment of that brand experienced, or the product experienced, so my view is, there are so many different places across the industry, that we could actually apply machine learning to, and my team is really excited about what we've been doing, especially in the next generation of supply chain. >> And it's also causing students to be really attracted to computer science, both men and women. My daughter, who is a senior at Berkeley, is interested in it, so you're starting to see the impact of machine learning is hitting all main stream, which is a good segue to my next question, we've been very passionate, I know it's one of your passions is inclusion and diversity or diversity and inclusion, there's always debates: D before I or I before D? Some say inclusion and diversity or diversity and inclusion. It's all the same thing, there's just a lot of effort going on to bring the tech industry up to par with the reality of the world, and so you have a study out. I've got a copy here. Talk about this study: Women in Leadership and the Priority Paradox. Talk about the study; what was behind it and what were some of the findings? >> Sure, and I'm excited that your daughter, that's a senior in college, is going to be another woman that's entering the workforce, and especially being in tech, so the priority paradox is that we actually looked at over 2,300 organizations, these are some of the top institutions around the world, that are curating and attracting the best talent and skills. Now, when you look at that population, we were surprised to find out that you would think by 2019-2018 that only 18% of those organizations actually had women in senior leadership positions, and what I categorize as senior leading positions, are in the see-swee, as vice presidents, maybe senior executives or senior managers; director level folks. So, that's one piece, which is, wow, given the size and the state where we are in the industry, only 18%: we could do better. Now, why do we believe that? The second piece is, you want the full population of the human capacity to think and creatively solve. Some of the world's biggest complex problems; you don't want a small population of the world trying to do this, so, the second piece of the paradox, which was the most surprising, is that 79% of these companies actually said that formalizing or prioritizing gender, fostering that kind of inclusive culture, was not a business priority, and that they had a harder time actually mapping that gap. Now, in the study, what we actually discovered though, was those companies, that did make it a priority, actually had first mover advantage, and making it a priority is quite simple. It's about understanding how to create that inclusive culture, to allow different perspectives and different experiences to be allowed in the co-creation and development. >> So, first mover advantage, in terms of what? >> Performance, actual business performance, so even though 80% of the organizations that we interviewed actually said that they've not made it a business priority, the 20% that did, we actually saw higher performance in their outcomes, in terms of business performance. >> So, this is actually a business benefit, too. I think your point is, the first mover advantage is saying, those companies that actually brought in the leadership to create that different perspective, had higher performance. >> Absolutely. >> We've talked about this before; one of the things I always say is that, tech is now mainstream, and it's 18% of the target audience of tech isn't the market, it's 50/50 or 51. Some say 51% women/men, so who's building the products for half the audience? So, again, this doesn't make any sense, so this is a good statistic. >> It is, and if you think about the students that are actually graduating out of graduate school, recently, there's actually more women graduating out of grad school than men. When you think about that population that's now entering the workforce, and what's actually happening through the pipeline, I think there's got to be thoughtful focus and programmatic improvements across the industry, around how to develop talent and make sure that different companies and organizations can move. Like you said, problem solve for creating new products that actually serve the world, not just serve certain populations, but also do it in a way that's thoughtful about, kind of, the makeup. >> And the mainstream and prep of tech obviously makes it more attractive, I mean, you're seeing a lot more women thinking about machines, like my daughter, the question is, how do they come in and not lose their footing, mentor-ship? So, what are the priorities that you see the industry needs to do? What are some of the imperatives to keep the pipeline and keep all the mentoring, obviously mentoring is hot, we see the networking built. >> Yeah, mentoring is huge. >> What's your thoughts on the best practices that you've been involved in? >> Some of the best practices we've actually done a number with an IBM, we've done a program called, Tech Re-Entry, so women that have decided to come back into the tech workforce, we actually have a 12 week internship program to do that. Another is a big initiative that we have around P-TECH, which is the next generation of workers aren't just going to have a formal college and or PHD masters type degrees. The next generation, which we're calling, is not necessarily a white collar, blue collar, what we're calling it is, new collar, meaning these are students that are able to combine their equivalent of a high school degree and early college education in one to be kind of, if you think about it, next generation of technical vocational schools, right? That quickly enter the workforce, are able to do jobs in terms of web development, in terms of cloud management, cloud services, it could be next generation of-- >> It's a huge skill gap opportunity, this is a big opportunity for people. >> It is, and we're seeing great adoption. We've seen it on a number of states across the US, this is an effort that we partner with, the states and the governors of each state, because public education has got to be done in a systematic way that you can actually sustain it for many, many years and this is something that we were excited about championing in the state of New York first. >> The ReEntry program and other things, I always tell myself, the technology is so new now you could level up a lot faster than, there's not that linear school kind of mentality, you don't need eight years to learn something. You could literally learn something pretty quickly these days because the gap between you and someone else is so short now, because it's all new skills. >> It's true, it's true. We talk about digital disruption through the lens of businesses, but there's a huge digital disruption through the lens of what you're talking about, which is our individual development and talent, and the ability to learn through so many different channels that's available now, and the focus around micro degrees, micro skills, micro certifications, there's so many ways for everyone to get involved, but I really do encourage everyone across every industry to have some knowledge and basis and understanding of tech, because tech will redefine how services and products are delivered across every category. >> And that's not male or female: that's just everyone. Again, back to technology for good, we can solve technology problems, You guys have been doing it at IBM, solve technology problems, but now the people problem is about getting people empowered, all gender, races, et cetera, the people getting the skills, getting employed, working for clouds, this is an opportunity. >> This is a huge opportunity. I think this is an exciting time. We feel like we're entering this next phase of, what I call, chapter two of cloud, this is chapter two of digital reinvention, of the enterprise, digital reinvention of the individual, actually, and it's an opportunity for every country, every population group to get involved, in so many new and creative ways, and we're at the early foundation stages in terms of both AI development, as well as new capabilities like Blockchain. So, it's an exciting time for everybody. >> Well, that's a whole nother topic. We'll have to bring you back, Inhi. Great to see you, in fact, welcome to Palo Alto. First time in our studio. Let's co-host something together, me and you. We'll do a series: John and Inhi. >> I would love that. That would be fun. I'm excited to be here. >> You can drop by our studio anytime now that you live in Palo Alto, we're neighbors. Inhi Cho Suh here, general manager IBM Watson, customer engagement, friend of theCUBE, here inside our studios, Palo Alto. I'm John Furrier, thanks for watching. (upbeat music)

>> Interviewer: Live from Las Vegas, it's the Cube, covering IBM Think 2018. Brought to you by IBM. >> Hello everyone welcome to the Cube, I'm John Furrier, we are here in Las Vegas for the Cube coverage of IBM Think 2018. So Cube Studios, live coverage, all day long three days, this is our third day, our next guest, is Cube alumni, Inhi Cho Suh, she's also the general manager of Watson Customer Engagement, been on so many times I don't know, eight, ten, a lot, you're a VIP. Great to see you. >> Thank you, good seeing you John, I really enjoy hanging out with you guys. >> So we love to hear what you're up to, cause you always have your finger on the pulse, here at IBM, take a minute to explain the group that you're in, Watson Customer Engagement, that's kind of a nice bumper-- but there's a lot to it, you're doing now. >> There is. >> It's large it's got billions of dollars in revenue, give us the numbers, run the numbers for us, size, people, products, all in 30 seconds, no go. >> It's an exciting space. So Watson Customer Engagement is really a Watson business applications, that are relevant for marketers, merchandisers, digital commerce leaders, as well as supply chain professionals. So my team really develops the software, both for on premises and SasS for everything from digital marketing experiences, personalized marketing, campaign management, to managing next generation of interactive sites and shopping sites, to understanding customer journeys, and journey analytics, so supply chains, and big big collaborations. So it is a pretty broad breadth of about 21 solutions in offerings, that span many industries and many countries. >> We you got your hands in a lot of great stuff across the board but I think the big news today was the blockchain announcements, you guys featured a solution on stage, this is hard news, so explain, so talk about the hard news, you have an announcement, it's on stage, it's blockchain related, >> Yup absolutely so my team has been working on creating more analytics in our supply chain solution. So one of our solutions is called Supply Chain Insights which really is about adding visibility to disruptions. And being able to apply analytics to let's say management response, incident management. Then we were thinking about our supply chain business network, so that is a separate offering that we have, which is about 6 thousand clients are on it. With 400 thousand trading partners, we do 8 million transaction documents a day, in terms of this trading network. What we did was we announced a shared visibility ledger, for any of our clients and partners, in the supply chain business network. So we're adding blockchain to that as a way to ensure that transparency, as well as speed of operations, so we're really excited about it >> And security. >> And security huge. >> Huge. So supply chain, blockchain, value activities, all this stuff, this is where blockchain shines, because this is a core competency of IBM, for generations. >> Oh absolutely. >> I mean providing applications for value chains, so this is interesting, so just to get the clarification the product is on preview? >> Yeah it's a technology showcase that we're doing right now that we've prototyped, and we're going to make it available as an offering that's called shared ledger, for any client that's actually on our supply chain business network today. >> And what's in it for them? How do they implement it, and the vision of the product, they already have a product, they bolt in on, is this a new offering? >> Yeah so if they already have it, they'll get access to let's say a visibility layer, so the shared ledger will allow you to see where in the process your transaction document is. So let's say you're in the area of consumer and merchandising and moving goods. From in transit. So knowing when a box actually left a particular warehouse, is it in transit or not and did it actually deliver on time. There's a lot of parties involved in all of that. >> And paperwork, and manual processing, data entry >> You got it. Now you have the actual stamped records, of who's touched it, when, and whether or not with IOT instrumentation too. Of when things have moved or not. >> So this brings up the conversation we've been having on the Cube about the inefficiencies now going to be abstracted away with things like blockchain and AI. Used cases that you've seen that jump out at you, that you'd like to share, that can highlight that, obviously AI, I said analytics, that's your wheelhouse. Now blockchain's emerging, I mean this is the innovation sandwich. AI on one hand is bread, and then you got blockchain, and data's the meat. >> Well you know especially in areas like supply chain, where small bits of optimization, meaning a one percent improvement, or resolving invoice and settlements, have such huge ripple effects downstream. So there was a great example in terms of our Maersk work, and global trade and blockchain. Is food shipments in particular, and food safety. And being able to resolve the source of where the original food, whether it was grown, or harvested, and being able to do that in seconds, not weeks, right, going through that paperwork. So there's huge opportunities there. We're excited because we're now adding in not just AI capabilities, but we're also adding in collaboration capabilities into that, which then allow groups of people to interact together, in time, just in moment, to address alternative decisions and routes. >> Inhi I want to get your personal perspective on something, we've had so many conversations in the past around points in time, show messaging, and products you're announcing, it seems like this show at IBM, with everything coming together under one big tent, you see visibility now on unit economics of value, you're starting to see the path towards solutions, for customers, it's not as foggy as it once was. How do you explain that, you've see this evolve, and Jamie Thomas and I were talking earlier about, you know we base an investments and bets is now paying off what's really happening here, what's the big ah ha moment, where all this is kind of crystallizing right now. >> Well a couple things have happened. You know IBM's gone through, we've gone through our own transformation. If you think about even four or five years ago, the mix of our portfolio, to what it is now, less than I would say three billion of our revenue basis was in the mix that we have now. And if you think about our fourth quarter earnings even as we enter first quarter, we had I think over 46 percent, 46 to 48 percent of our portfolio tied to what we call our strategic imperatives. And that's a huge transformation, so part of that is a couple things, one is, we said look, this world of AI leverages and consumes a tremendous amount of data, and we want to make sure that you're protecting your data set. So we want to be thoughtful about how you engage strategically so let's have your strategy, let's make sure you understand your data, we want to protect you in that. We want to actually enable you to curate, train, harvest, the insights from that. We want to make sure we leverage your expertise. So your people, your talent, so augmenting them with capabilities that are work flow oriented, task management, self discovery, and then most importantly, delivering platforms multiple platforms quite frankly, over time that learn. Right, learn to interact, and evolve and can integrate these data sets, in order to give our clients speed. So that's what's been great about here, is we're actually getting to share our own transformation story, but also our portfolio has evolved across strategy, data, and platform. >> It's been sure and a clear line of sight on some value. What's the big bets that you could look back on the past five years and say wow, we made some big bets, these one's paid off. What were those big bets in your mind. You've been involved in a lot of deals I know, analytics side, what were the big bets that IBM made that's paying off right now? >> You know I feel like I've known you almost eight, nine years now right, since you guys started on some of this. I would say for example, our better round big data. That is a huge bet, in terms of our analytics capability, and that is a full spectrum, that is something that we've been investing in for quite a long time. And then when you think about the bet on Watson and AI, and transforming, not just businesses and business process but actually transforming professions. We have Watson today operating across multiple industries, like 20 different industries in 45 countries. Multiple languages, multiple implementations, and it's getting better and better, whether it's healthcare, it's tax accounting, it's law and cyber security, we're seeing huge opportunities >> Data paid off big time. >> Huge payoff. Cloud. Cloud is huge for every client, because they're in different states of their journey. There may be certain application workloads, that they want to manage themselves, there maybe be applications that they want, and services that they want to subscribe to in the cloud. Public, private, hybrid, we're having that dialogue. So I think everyone is on that journey now. So that's another huge bet. And then verticalizing the application sets. And so one of the things that I've got the opportunity to be a part of right now, is really the business applications, and how are we infusing Watson into our business applications. >> And leveraging the horizontal scale of Cloud, and everything else, and blockchain. So what's the priorities for you going into the new business, you got a big organization, thousands of employees, or people work for you, a lot going on, what's the priorities, what is the focus? >> I've got about five thousand people on the team, so small team (laughs) Globally dispersed, we're working on a number of things actually, and what's so exciting about that is we're thinking about personalizing AI at mass scale. So when you think about, through the lens of a marketer, real time personalization is becoming more, and more challenged, because of not only the data sets, but the types of tools and the varied tool applications, you're switching context all the time. So we're providing ways to integrate and mix data sets, so our user behavior exchange data set really gives insights around consumer sentiment, behavior, and context. The work the team has been doing around metropolts, hyper local store and a city location data, mixing that with events and other activities, and customer transaction data. So a lot on that front. The second category we're really focused on, is next generation of embedding, what I would consider cognitive services, like search, headless search, so really understanding intent that's pervasive, on other platforms. We're adding things also, like embedded agents, so everyone's right now talking about you know they want to create chat bots, and bots, But they may be embedded in systems, and they also may be embedded in different types of use cases, call center, so forth, so we're excited about that. And then obviously the supply chain area with blockchain, so we've got a lot. >> And the payoff in data's interesting because now you've got contextual relevance for things that are embedded, like chat bots, or whatever at the right time. And also if you think about the gamification opportunities, data now in these network affect markets, whether it's blockchain evolving into cryptocurrency, and decentralized web applications. The commerce piece is going to be impacted. Your vertical integrations are going to be gamified. This is coming right down main street for IBM isn't it? >> Well and if you think about blockchain one of the biggest challenges is onboarding into a network. So what we're trying to do is one of the use cases is actually adding blockchain to existing networks, and so that once you're onboarded into a network, you can connect to other networks. So a network of networks sort of effect. >> And their effects is all data driven. >> It's all data driven. So membership and governance around blockchain is important, and then the other piece we're thinking through is use cases by vertical, so retail, so when you go through that lens, and retail in terms of fashion, it's a very different lens than when you think through the business lens of retail banking, right. And our team is thoughtful about what does that mean in the next generation of content services. So how do you automatically tag images, and surface them up, for it be published in the right media form, independent of the channel, or the navigation tools or assets. There's a lot here I'm excited. >> So final question for you, it's kind of a philosophical one, you can answer it or not. You know you always get the zingers from me, but the tools are changing too, so in these new emerging markets, where there's just not-- take finance for instance and say cryptocurrency, and software, the tooling's not there, you can't just stand up at a trading exchange, that's in these new token environments, or what these apps have. So there's new tooling coming out, that's a concern, how are you guys helping customers get the tooling? Is that on your radar? Is that something you guys are talking about? >> Well you know it's interesting that you bring it up, which is technology adoption. I'm just going to call it in a broader sense, because part of tooling is really about in user education and enablement. We are actually adding a capability called Ask Watson, embedded in our software and services, especially our SasS properties, such that hey, I want to build a new email campaign, well what are my choices, and instead of reading through a traditional manual, or having to go and find someone, or watching a bunch of YouTube videos, what if Watson actually surfaced, here are ways here are some existing templates, where would you like to start. And all of a sudden this kind of co-creation happens. So we're actually thinking of applying Watson, embedded in our software, and SasS services to enable, not just tooling, actually automatic assistance in the task, in the moment. >> Yeah no need to code. Insights is a service. >> Huge, customer insights is actually one of our top applications. So we're doing capabilities around journey analytics, and customer experience analytics, so think about when you're any business person, who's got a set of clients, you know what they want to do as they express their brand, it may be done through email communications, it may be push notifications, there may be a SEO notification, and in that scenario, at what point, does the consumer, or the be to be struggle, in actually fulfilling a transaction. Was it as they're zooming in and doing product comparisons was it as they were looking at post purchase serviceability. We are able to actually understand and look at their journey as they travel through all these touch points. So we're actually doing customer experience analytics, too. So for me, just coming from that data analytics background, into this application space of so many domain practitioners, >> And these applications got to be real time, they got to have the data analytics. Inhi, great to see you, thanks for coming on the Cube, it's been eight, nine years, it feels like in analytics years it's like 20. You look great, thanks for sharing your insights, on the Cube and congratulations on your new role, >> Thank you >> Thanks for stopping by the Cube. I'm John Furrier here in the Cube Studios, IBM Think 2018, back with more coverage after this short break.

okay we're back live here inside the cube rounding out day one of exclusive coverage of IBM information on demand I'm John further the founder SiliconANGLE enjoy my co-host Davey lonte we're here in heat you saw who's the vice president I said that speaks that you know I think you always get promoted you've been on the cube so many times you doing so well it's all your reason tatian was so amazing I always liked SVP the cute good things happen that's exactly why i be MVP is a big deal unlike some of the starters where everyone gets EVP all these other titles but welcome back thank you so the storytelling has been phenomenal here although murs a little bit critical some of the presentations earlier from gardner but the stories higher your IBM just from last year take us through what's changed from iod last year to this year the story has gotten tighter yes comprehensive give us the quick okay quick view um okay here's the point of view here's the point of view first you got to invest in a platform which we've all talked about and i will tell you it's not just us saying it i would say other vendors are now copying what we're saying cuz if you went to strata yes which you were there we were there probably heard some of the messages that's right why everybody wants to be a platform okay one two elevated risk uncertainty governance I think privacy privacy security risk this is what people are talking about they want to invest in a more why because you know what the decisions matter they want to make bigger beds they want to do more things around customer experience they want to improve products they want to improve pricing the third area is really a cultural statement like applying analytics in the organization because the people and the skills I would say the culture conversation is happening a lot more this year than it was a year ago not just at IOD but in the industry so I think what you're seeing here at IOD is actually a reflection of what the conversations are happening so our organizations culturally ready for this I mean you guys are going to say yes and everybody comes on says oh yes we're seeing it all over the place but are they really ready it depends I think some are some are absolutely ready some are not and probably the best examples are and it really depends on the industry so I'll give you a few examples so in the government area I think people see the power of applying things like real-time contextual insight leveraging stream computing why because national security matters a lot of fraudulent activity because that's measurable you can drive revenue or savings healthcare people know that a lot of decision-making is being made without a comprehensive view of the analytics and the data now the other area that's interesting is most people like to talk about text analytics unstructured data a lot of social media data but the bulk of the data that's actually being used currently in terms of big data analytics is really transactional data why because that's what's maintained in most operational systems where health systems so you're going to see a lot more data warehouse augmentation use cases leverage you can do on the front end or the back end you're going to see kind of more in terms of comprehensive view of the customer right augmenting like an existing customer loyalty or segmentation data with additional let's say activity data that they're interacting with and that was the usta kind of demo showing social data cell phone metadata is that considered transactional you know it is well call me to record right CDR call detail records well the real time is important to you mentioned the US open just for folks out there was a demo on stage when you guys open data yeah at all the trend sentiment data the social data but that's people's thoughts right so you can see what people are doing now that's big yeah you know what's amazing about that just one second which is what we were doing was we were predicting it based on the past but then we were modifying it based on real time activity and conversation so let's say something hot happened and all of a sudden it was interesting when Brian told me this he was like oh yeah Serena's average Twitter score was like 2,200 twit tweets a day and then if some activity were to happen let's say I don't know she didn't he wrote she had got into a romance or let's say she decided to launch a new product then all of a sudden you'd see an accused spike rate in activity social activity that would then predict how they wanted to operate that environment that's amazing and you know we you know we love daily seen our our crowd spots be finder we have the new crowd chat one and this idea of connecting consumers is loose data it's ephemeral data it's transient data but it's now capture will so people can have a have fun into tennis tournament and then it's over they go back home to work you still have that metadata we do that's very kind of its transient and ephemeral that's value so you know Merv was saying also that your groups doing a lot of value creation let's talk about that for a second business outcomes what do you what's the top conversation when you walk into a customer that says hey you know here's point a point B B's my outcome mm-hmm one of those conversations like I mean what are they what are some of the outcomes you just talked to use case you tell customers but like what did some of the exact you know what I'll tell you one use case so and this was actually in the healthcare hotel you won healthcare use case in one financial services use case both conversations happened actually in the last two weeks so in the healthcare use case there's already let's say a model that's happening for this particular hospital now they have a workflow process typically in a workflow process you you're applying capabilities where you've modeled out your steps right you do a before be before see and you automate this leveraging BPM type capabilities in a data context you don't actually start necessarily with knowing what the workflow is you kind of let the data determine what the workflow should be so in the this was in an ICU arena historically if you wanted to decide who was the healthiest of the patients in the ICU because you had another trauma coming in there was a workflow that said you had to go check the nurses the patient's profile and say who gets kicked out of what bed or moved because they're most likely to be in a healthy state that's a predefined workflow but if you're applying streams for example all the sudden you could have real-time visibility without necessarily a nurse calling a doctor who that calls the local staff who then calls the cleaning crew rate you could actually have a dashboard that says with eighty percent confidence beds2 and ate those patients because of the following conditions could be the ones that you are proactive in and saying oh you know what not only can they be released but we have this degree of confidence around them being because of the days that it's coming obvious information that changes then potentially you know the way your kind of setting your rules and policies around your workflow another example which was really a government use case was think about in government security so in security scenarios and national security state there is you never quite know exactly what people are intended to do other than you know they're intending something bad right and they're intentionally trying not to be found so human trafficking it's an ugly topic but I want to bring it up for a second here what you're doing is you're actually looking at data compositions and and different patterns and resolving entities and based on that that will dictate kind of potentially a whole new flow or a treatment or remediation or activity or savior which is not the predefined workflow it's you're letting the data actually all of a sudden connect to other data points that then you're arriving at the insight to take the action where is completely different I wanna go back to sleep RFI course not healthcare examples yeah so where are we today is that something that's actually being implemented is that something they sort of a proof of concept well that's actually being done at it's being done in a couple different hospitals one of which is actually in hospital in Canada and then we're also leveraging streams in the emory university intensive Timothy Buckman on you did earlier oh yeah the ICU of the future right absolutely brilliant trafficking example brings up you know Ashley that's the underbelly of the world in society but like data condition to Jeff Jonas been on the queue as you know many times and he talks with his puzzle pieces in a way that the data is traveling on a network a network that's distributed essentially that's network computing I mean estate management so look at network management you can look at patterns right so so that's an interesting example so that begs the next question what is the craziest most interesting use case you seen oh my gosh okay now i got i think about oh yes and you can talk about and i can talk about that creates business value or society value oh you know I okay um for you are putting me on the spot the craziest one so 3 we could be great could be g-rated don't you know they go to 2k yeah you know what I participated three weeks ago tiaa-cref actually hosted a fraud summit where it was all investigators like they were doing crime investigation so more than sixty percent of the guys in the room carried weapons because they were Security Intelligence they were pleased they were DA's they repented I was not packing anyway and there was about so 60-plus percent were those right and then only about thirty percent in the room were what i would consider the data scientists in the room like these are the guys are trying to decide which claims are not true or false so forth there were at least like three or four use cases in that discussion that came out they were unbelievable so one is in the fraud area in particular and in crime they're luring the data there what does luring the data they're taking location-based data for geographic region they're putting crime data on top of that right historical like drug rings and even like datasets in miami-dade county the DA told me they were doing things where rather than looking at people that are doing the drugs they they realize people that had possession of a drug typically purchased within a certain location and they had these abandoned properties and were able to identify entire rings based on that another one this is also semi drug-related is in the energy utility space there was in the middle part of the United States houses in Nice urban areas where they were completely torn apart on the interior and build into marijuana houses and so of course they're utilizing high levels of gas and electricity in order to maintain the water fertilization everything else well what happens is it drives peaks in the way that the energy utility looks on a given day pattern so based on that they're able to detect how inappropriate activities are happening and whether it's a single opportunistic type activity whether it's saying this was doing laundry or irrigating the Erie hey we well you know what's interesting about electricity to is especially someone's using electricity but no one's like using any of the gas you're like home but no one's cooking you know something's a little long but it was fascinating i mean really fascinating there were like several other crime scenarios in terms of speed i actually did not know the US Postal Service is like the longest running federal institution that actually tracked like mail fraud and one of the use cases i'm sure jeff has talked about here on the cube is probably a moneygram use case but we talked about that we talked I mean it the stories were unreal because I was spending time with forensic scientists as well as forensic investigators and that's a completely do we're getting we're getting the few minutes need for a platform to handle all this diversity so that's the security risk the governance everything you gotta go cuz your star for the analyst me I can't watch this conversation one final question one of the best yet as we get drugs in there we got other things packing guns guns and drugs you in traffic you know tobacco if you go / news / tobacco well write the knowledge worker all right final question for I know you gotta go this big data applications were you know the guys in the mailroom the guys work for the post office are now unable to actually do this kind of high-level kind of date basically data science yeah if you will or being an analyst so that what I want you to share the folks your vision of the definition of the knowledge worker overused word that's been kicked around for the PC generates but now with handheld with analytical real-time with streaming all this stuff happening at the edge how is it going to change that the knowledge work or the person in the trenches it could be person the cubicle the person on the go the mobile sales person or anyone you know I some people feel threatened when they hear that you're going to apply data and analytics everywhere because you're it implies that you're automating things but that's actually not the value the real value is the insight so that you can double down on the decisions you want to make so if you're more confident you're going to take bigger bets right and decision-making historically has been I think reserved for a very elite few and what we're talking about now is a democratization of that insight and with that comes a lot of empowerment a lot empowerment for everyone and you don't have to be a data scientist be able to be able to make decisions and inform decisions if anything you know actually Tim Buckman I had a good conversation about them as a professional you know what I if I was a physician I'd want to work at the hospital that has the advanced capabilities why because it allows me as a professional physician to then be able to do what I was trained to do not to detect and have to pay attention to all these alarms going off you know I want to work at the institutions and organizations that are investing appropriately because it pushes the caliber of the work I get to do so I think it just changes the dynamics for everyone tim was like a high-priced logistics manager you want to work with people want to work with leaders and now we're in a modern era this new wave is upon us who care and they want to improve and this is about continuing to improve Dave and I always talk about the open source world that those principles are going mainstream to every aspect of business collaboration openness transparency not controlled absolutely absolutely Indy thanks so much for coming in the queue and know you're busy think of your time we are here live in the cube getting all the signal from the noise and some good commentary at the end a one we have one more guest ray way right up next stay tuned right back the queue