JAMES OWENS: Well, good evening, everyone. Welcome to snowy New York. I'm just here from the Rockies; I've been praying for snow every day. Get here tonight, and it may be here for a few days. I hope not.
Anyway, welcome to the Council on Foreign Relations, and our 2013 Corporate Conference. I'm Jim Owens. I chair the council's Committee on Corporate Affairs. And certainly, I'd like to thank all of you for being here this evening.
As you might know, this marks the 60th anniversary of the council's Corporate Program, a program which began in 1953 with just 25 members, some of who are here tonight: BNY Mellon, City, Exxon Mobil, Freeport-McMoRan, GE and, prominently, IBM. And they're all still members today. They've now been joined by nearly 170 other global brand-name corporations in a thriving and fully integrated program that really has a big impact on the life of the council. Corporate members enjoy a robust program of benefits, including access to more than 300 meetings a year in New York and Washington and other cities around the country, and the ability to participate virtually from all over the world.
We're especially proud of our CEO Speaker Series, which in recent months has hosted Boeing's Jim McNerney, J.P. Morgan's Jamie Dimon, Exxon Mobil's Rex Tillerson and Chevron's John Watson. And we're pleased tonight that we'll be adding IBM's Ginny Rometty to this CEO distinguished speaker list.
The Corporate Program means to provide a unique forum for senior executives as member companies connect to the foreign policy debate through the council. The business community certainly has enormous stake in this foreign policy debate and, really, few places to discuss it, particularly with the kind of interface with our public officials that the council provides.
Our meeting session tomorrow with Roger Altman and Richard Haass will explore competitiveness in more detail, and we'll talk a little bit more about that in the morning. But certainly, the ability of our country to lead in foreign affairs and in defense depends on our ability to compete in global markets. So that -- I think that will be a fascinating session.
We'll continue tomorrow with Henry Kissinger in conversation with Charlie Rose on geopolitical hotspots in the world. There will be a panel on the emerging demographic trends, and we'll close with the council's newest distinguished fellow, Tim Geithner, in conversation with Bob Rubin. We hope you'll take advantage of as many of these sessions as your schedule will allow.
Before we get into the evening, I'd like to take just a moment to thank council board members who are with us for this event, including our chair -- co-chair Bob Rubin, co-chair and vice-chair David Rubenstein, who's speechless tonight -- first time ever -- (laughter) -- and Tom Hill (ph) and Jami Miscik. Thank you all for being here. I'd also like to thank member companies for their contributions to the institution; a majority of those companies are represented at tonight's conference. We'd especially like to thank our founder-level members -- Bank of America, Merrill Lynch, Chevron, Exxon Mobil, Goldman Sachs, Hess Corporation, JPMorgan Chase, McKenzie and NASDAQ OMX. And last but certainly not least, I'd like to thank all of you for your participation in this annual corporate program. Without your engaged dialogue, questions, debate this program would be meaningless.
With that, Ginni, I'm pleased to be turning the program over to you. IBM was one of our founding corporate members, as I said earlier, and I couldn't be more pleased tonight then to have the new IBM chairman and CEO Ginni Rometty here to open this conference.
Ginni's been with IBM since 1981. She rose quickly through the ranks into a senior leadership position. She led the successful integration of PricewaterhouseCoopers's consulting arm into IBM beginning in 2002; she received the Carl Sloane Award in 2006 for that distinguished work. More recently, she has been critically involved with IBM's growth markets initiative, focusing on expanding IBM's reach into emerging markets around the world. It's expected that that will generate about 30 percent of the company's revenues this year. I've been very honored to be a member of IBM's board and to see Ginni's rise through the ranks and transition into her new role, and she's off to a terrific start.
And Ginni, welcome to the council. Thank you for being with us tonight. (Applause.)
VIRGINIA ROMETTY: Jim, thank you very much. And really, as well, to Richard -- you know, congratulations on your 60th anniversary here. And you mentioned, Jim, that we are one of the founding partners of the Corporate Program, but the history with the Council on Foreign Relations goes back to 1920 -- 1920s, so we've got a long history together here. So thank you for that.
And I'm going to start just with 10, 15 minutes of some comments here, and I'd like to begin them by reading to you, and ask you to consider three vignettes of recent events.
The first one -- a police department reduces the incident of rape by moving payphones inside of a convenience store.
Second one -- a Mexican cement maker launches its first global product in record time not by building a factory but by building a social network.
And the third -- a U.S. presidential campaign doesn't rely on opinion polling and yet predicts the final vote in a key swing state within 0.2 percent.
Now, these may seem -- you may think, what am I doing; these are random, unrelated. But in my just short time, to get us started, I would like to convince you that these things are examples of the same phenomena: How organizations of any type -- and you represent companies, government entities, agencies, nonprofits, whatever -- will learn to compete in a new competitive landscape. And it's how they're going to compete, because five years ago -- Richard might remember, we had talked about -- we launched something called Smarter Planet, and in this room actually gave a talk about something that was seminal and emerging in the world. And now you hear the words -- you hear cloud, mobile, social network. However, ultimately, this is going to be about the data that is generated by all of this. And I would like to assert -- and I hope we're going to talk more about this -- that data will be the basis of competitive advantage for any organization that you run. It will be the basis in what will be a smarter era -- that it will be the basis for competitive advantage.
And I'd like you to think of data as the next natural resource -- the only limit is yourself, though; it's not limited -- the next natural resource that can be to our era what we think of -- go back in time, and you think about steam, oil, electricity did to the industrial age. However, back then, just because you had access to those things did not make you a powerhouse. And the same will be true here: Just because you -- and that everywhere will have access, but what you do with it will make the difference. And so what will decide the winners and the losers? What will decide the winners and the losers?
And I want to share with you three principles that we've learned both with ourselves -- but actually by doing work with thousands around the world on this topic -- both companies, governments and cities. So let me say that you would have to embrace three principles of the organization that you -- that you lead, if you are going to become a winner.
The first one -- it will change how you make decisions.
It will change how you in fact create value.
And the third is, it will change how you deliver value
So let me -- this sort of first principle -- changing how you make decisions. I'm going to assert that many, many more decisions in your company or entity, they will be based on predictive analytics and not your gut instinct or experience. Now, I say this for two reasons: one is because they can be based on all of this data. Sort of a factoid worth knowing: Every two days, the world produces as much data as all the world had created through the year 2003. And then we'll do this because we must, because many decisions have often led to some bad outcomes.
You know, we did a survey or risk managers not very long ago and asked the question, what was the number-one method you used in determining risk? What would you guess was the answer?
AUDIENCE MEMBER: Gut.
ROMETTY: Gut. It -- well, it was very -- senior management, intuition and experience -- as a gut. (Laughter.) Now, that would be another word for "gut." The other reason? You know, and this is -- this is not an unusual phenomenon. Even in -- even in fields that are very scientifically oriented, there's something called an anchoring bias. Those that are scientists in the room, it means you know two or three facts, they're in your subconscious; as you hear information and filter it, it guides the decisions you make, and you discount things that don't fit in that lens.
So it's why I told you the story about what turned out to be the Memphis Police. And that was a case like any -- it could have been any police anywhere in this world, in any city. And budget's tight; got to come up with a new approach. We did work with them -- with, in fact, University of Memphis. And the project was called CRUSH. Now, you might find that -- you know, CRUSH, police; the difference was, what CRUSH stood for was Crime Reduction Utilizing Statistical History. And what they were able to do was take sophisticated maps of data on top of each other, and then what you would see are patterns that were otherwise invisible. And the end of that story is finding the correlation where rapes were committed -- payphones outside; move them inside. And this is just one example of many, many that has led to a 30 percent reduction in crime in that city, largely because of this.
Now, you see this in industry after industry. I see it in how I run my own company -- but as well public sectors; many different cities around the world, you see it come to life.
But my key point on this is it's not about a technology tool. This at the end of the day is going to be about mindset and culture, because you have to -- people have to unlearn how to -- how to run a hospital, how to treat a patient, how to make a decision at work. And we don't teach these skills in universities today. We don't teach them, but we will.
Which leads me to my second point -- that again, I'd like to talk about more in our Q-and-A -- you're going to create value different. And what did I mean by that? I'm going to assert that the social network, the social network will be the new production line in a company, in an entity -- I don't mean in a consumer-alone world.
You might have forgotten this: Peter Drucker coined the word "knowledge worker." It was actually 1959 -- 1959, so I was a little toddler at this time. Now, non-routine work -- but what's changed? Obviously, I said tons of data. The tools are different today than they were then. Billions of different interfaces. But today's knowledge workers have access to something around the clock: The have access to each other. That's what's different. And in a social enterprise, I will also assert that your value will be not what you know; it will be what you share. And that is a very different paradigm.
And that's why the second story -- and that actually was about the Mexican cement maker CEMEX, a cement company -- first-ever global brand; I had to learn myself, actually -- many different kinds of cement. It all of course depends on the weather, the geology, the place, the part of the world. And they're often locally developed. In this case, with a social network of 50 different product development groups around the world, 400 communities, they launched a global brand in one-third the time it would have taken to do a local brand. So just a small example. But remember, this is -- this is a cement company that we're talking about. And what they're now valuing is expertise and experts.
And I see this in -- by the way, what it ends up doing to any company, any organization, it will change who you hire, how you compensate them, how you develop them. And in fact, I see it in IBM. You know, every IBMer today has access to -- boy, you name it; we have wikis, blogs, community, social networking and the like. But in the near future there will be something else, and I'm going to have IBMers -- they're not only going to rate each other; professionals, clients and the like will rate them. You'll be rated by the information you create, how you share it, what's its value. You know, you've seen this -- five stars. Maybe I'll even pay you that way. Five stars, one compensation; two stars, not. So it will be a different future.
And then the last point I'd leave you with is this idea that how you'll deliver value will be different. And value will be for individuals, not for segments. You know, all of us, whatever we do, we either try to reach a customer -- it could be a patient, it could be a citizen. And in truth, the best any of us do is a microsegment, some small amount. You might say, OK, males 17 to 25, this income level, this place, a red state, a blue state, with this characteristic. And even if you get it small, those are averages. They are averages.
And so what you will see with this rapid emergence of I believe big data, social mobility, you will in fact see the death of average, the word "average," and instead you'll see an era of you -- Y-O-U -- you. And that example is well written up in President Obama's campaign. It's well written up. It was not about targeting broad populations. Sixty-six thousand simulations were done a night, and out of that you decide where to put your resources. And that came out with the 0.2 percent in the famous state of Ohio, by having created persuadability scores -- individually, could you be persuaded -- and then orienting your resources that way.
And I -- this is not restricted to politics. If you have a call center, it's no longer about a script; it's about a dialogue. If you have -- if you're in advertising, it's not about a promotion; it's about a two-way discussion to get information. And in exchange, though, every one of us will expect something in return for that, in this new era -- some benefit, be that a citizen or an employee or a customer.
So just to get us started I wanted to just recap that this idea that in the future these guiding principles -- like I said, is we've learned them -- all around, creating competitive advantage in this new, emerging era. When it comes to decisions, they'll be made on predictive analytics and data. When it comes to creating value, the social network will be a production line. And when it comes to delivering value, it will be the individual; it will not be a segment.
But I'll end on this point. Actually, the challenge is not technology. As always, the challenge is culture. But remember, this is at the end-all about competitive advantage, be this a company, a country or a government entity. And in the end, I actually think something far more valuable will happen, because the greatest contribution of this shift will force every entity -- private, public, government -- to actually become an authentic organization.
So with that, I'd like to -- can I invite you up, Richard? Is that OK? (Laughter.) It's your party, but come up. (Chuckles.) So thank you, and I look forward to the dialogue. (Applause.) David, I love my tea. (Chuckles.)
RICHARD HAASS: This is an example of product placement, so if anyone is tempted to follow suit, let me know.
ROMETTY: (Chuckles.) (Inaudible.)
HAASS: Thank you. Thank you for that really interesting talk, and thank you and IBM for six decades of involvement.
I want to raise one question about the subject of date, if I could. And you used the phrase: It could lead to the death of the average. You don't worry at all that there's a danger in data, that data almost limits -- I was sitting there listening, and I was thinking of the Wayne Gretzky about you don't skate to where the puck is; you skate to where the puck is going to be. And can't reams of data get in the way? Doesn't data at some point almost force you inside the box and towards averages?
ROMETTY: You know, yes and no. Not if it's done at an individual level. And the other thing I think data does more than anything is it removes biases that I talked about that you have. And we're actually seeing this with work we've done -- many of you may have seen it with some work we've done with -- it's a longer story, but a computer named Watson, in medicine. And at the end of the day, because it is so unbiased and unfiltered in how it looks at information, it comes up with different proposals you wouldn't otherwise have come up with.
Now, all that said, my view is this is not an either/or. So it's going from one extreme; there's always a ditch on both sides of a road. And in this case and many times, you've got to take the data as input. There will be times when you take it for the answer. But often, it will be to make you think of something different.
So I do think you have to be careful. People say, well then, is that thing just going to replace everyone? Not at all. If anything, it's giving you advice. In fact, I envision -- actually, Richard, it's a day where often what you're going to find out is a set of alternatives, confidence levels, facts that either support them or things that don't. That's actually what the data is going to show you. And then you add creativity and innovation to that.
HAASS: I should basically say, by the way, that those of you who are hoping that David Rubenstein was going to interview Ginni, I apologize for the disappointment. David was felled by an inability to speak. So those of you who want to have an argument with him or about what Carlyle is doing, tonight is your best opportunity. So I recommend you all accost him --
ROMETTY: I get a rain check with him, though?
HAASS: Yeah, you get a rain check. (Laughter.) When I -- when I think of the phrase IBM, I think of chess, computer playing chess; I think of mainframes, Big Blue. I expect much of that is decades if not longer out of date. What is IBM now?
ROMETTY: Yeah, that's -- you know, so when you're over a hundred years, you have lots of lessons you learn, right? And I would say one of the biggest lessons we have learned in the hundred years is don't define yourself by a thing, that that's a mistake. Don't define yourself by a product at any one point in time. So if you asked me to put it in a word, I'd -- I feel what IBM is an innovation company, so it's a company that continuously transforms to become something else that's of higher value.
So what you remember would have been right. I mean, decades ago we were a hardware company. But you look today, and the hardware business represents 15 (percent) to 20 percent of our business today. So it's a complete 80-20 flip from where it has been. But that's always just been about a search of finding what's the next area where you can make a market and contribute.
HAASS: Well, I want to talk about that, because I'm curious then to the extent now that IBM is not a hardware company, but it's a technology --
ROMETTY: Includes hardware -- important -- but much more --
HAASS: It's technology, it's services, it's many things. There's not a -- somewhere in there, it has to be embedded some assumptions about the dominant technologies, either what they are or what they're going to be. When we had Randall Stephenson in here a few years ago, it reminded me of a scene out of the movie "The Graduate." And he said, I've got one word for you all. And we all hung on. It was not "plastics." It was "mobility." And everybody took note.
So when you look at technology today, what is your sense of what it's shouting at you?
ROMETTY: Yeah, I think the -- it's actually -- what it's shouting is a confluence of four things happening faster than they've ever happened in the past. So it's a bit different than the past, where there'd been one thing, as you said. Now, you've got these phenomenas. And it's not so much what they are technology, it's what they enable, which I'll come back to. But you've got cloud, mobile, social and big data coming off of all of those things. But they're all at one time and they're all happening fast. And so what happens as a result of that, as an example?
So as I say, this is going to force new ideas. You see it already. I know many of your businesses, the business people I know here, it's going to force a whole change in what I would call affectionately the front office of a company. So professions like marketing are going to be completely redone -- because this is enabled, and how they're going to use technology. You'll enter an era where in the past people worked on their back office; now they're working on their front office, in this complete -- like I say, there's -- it's quite obvious marketing is one of those professions about the individual -- a dialogue, a complete -- by the way, this is why marketing is going to be such a steward of the culture of a company, because of -- you're going to be transparent to people out there, to your customers, what you are. So those things that one time are really one of -- that is the next big thing.
Now, from a -- if I could just -- one more plug -- from an actual "big T" technology perspective, there is a third wave of technology happening at this same time. It's related to data. But let me -- if I describe it, I think it will make perfect -- I hope perfect sense. To date, there have been two eras of technology in all of the world, in all of time. The first era were computers that counted things -- I think that's quite obvious -- tabulation of all different kinds. The second era were computers that were programmable. You tell them what do to: If, then, do this. And some of them do that -- at millions and millions a second they do that, or do multiples in one time.
The third era will be -- because of data, it has to be this is a computer that learns. You can't -- the information's too big, it's too fast, you can't program it -- that we'll keep talking about security, all these different things. You have no choice. It will be a system that -- you can use the word "cognitive;" it has to learn by itself. And that's the third wave. Each of these go 30 (years) to 50 years. That's the wave that starts now. And it coincides with that big data. And that to me is a long -- decades-long change that will happen, those two together.
HAASS: But two of the other words you mentioned were "cloud" and "social media." So your sense is, where you sit at IBM, that these are not, if you will, passing phenomena, but these are -- these are, if you will, the new normal?
ROMETTY: I think they're the new normal. And you know, we've got 430,000 people; 50 percent or so have been with us less than five years. So you see another -- and in some cases it's generational; you see a millennial generation out there, and how they work and what they do differently, and every one of us are going to -- the next workforce, it -- well, you know, you see it if -- around you, right? I don't tell you something you don't know. And so these phenomena absolutely change how people think, how they work, how they want to work, how they're going to interact.
So to me, these could be very powerful inside the organization. We were talking over some coffee right before, and I was saying I use these technologies internally on how -- you know, we were saying how do you deal with a -- such a large workforce? And these have allowed me to accomplish what I think in an old way of doing, communicating, would take someone years to do. You're able to move that maybe people almost in a one-to-one relationship by doing that within your company.
HAASS: Given the dynamism that you're describing and the fact that we could be moving -- you've got movement both within eras and possible from one era to the next -- what about that worries you? What keeps you up at night, then?
ROMETTY: Again, so given our history and long -- and you reflect back, what did you learn? In this industry, technology -- most people characterize technology as a very hyper industry. Innovation commoditizes. Innovation commoditizes. So the biggest thing to fear in this industry is you miss a shift and --
HAASS: What do you mean by a shift?
ROMETTY: A shift, a technology shift. And if you go back in -- you mentioned it yourself, about different eras. You actually started down that path. The -- I came and said them in a big, broad technology sense -- things that were tabulating, programmable. Well, those manifested themselves over time in -- probably the first era of real computers people remember would have been mainframe; you mentioned mainframe. IBM was by far the leader in that era. But then there was client server that came after that. And we were -- again, we were speaking about this, too. Well, we played a role, but we weren't the dominant player in that. And that's the time where IBM almost met its demise, during that period. And so that's what happens when you miss a shift.
Then came Web -- sort of the initial Web 1.0, of which we participated in some very big ways from an enterprise, a company perspective -- not the consumer. And then now you'll meet this new wave, sort of when you add all four of these happening at one time together. So you don't want to be late. You don't want to miss it.
HAASS: When I think of technology now, I think of the Palo Alto gang and I think -- or out West, and you think of the Apples, the Googles and others. Is IBM -- are you still -- when the best graduates come out of the schools, essentially, what is it you do to get them to come to your campus rather than theirs?
ROMETTY: Yeah. You know, to me, in a word, when people come to IBM they come to IBM because you can work on the world's most important problems, with access everywhere in the world to everything. And IBM is really the only one left with a commercial research organization -- the only commercial research organization in our industry left, well over 3,000 -- and I mean real research; not development, real research, all right? So hiring the majority of the world's Ph.D.s in math, as an example, to join on. So that idea that you can work on the most important things, whether it's landing a man on the moon, whether it's right now the work we're doing -- as you well know, Richard -- with Memorial Sloan-Kettering, with MD Anderson, Cleveland Clinic on oncology and cancer. You don't get to solve -- those are grand challenges. You remembered Garry Kasparov and chess; that's what you were referring to. These are grand challenges. And the chance that you get to impact one of those -- you know, those are dreams of a lifetime to get to work on. So it is typically the challenge and the people, are why they come.
And you know, there's also a second reason. Many of those -- we are an enterprise company; and that's a choice, to work on enterprises, not consumers. So -- and that's a set -- a different set of problems.
HAASS: I'm going to ask a few more questions, then I want to open it up to you. One issue I wanted to put on the table is cyber. We as an institution had some unfortunate experience two months ago --
ROMETTY: Yes -- I know, I know --
HAASS: I expect some of the organizations here -- and I expect every organization here is spending unimaginable sums of time and money making themselves less vulnerable -- you never use the word "invulnerable;" simply less vulnerable. Some have been more or less successful than others. What is your involvement in this space?
ROMETTY: Look, we -- from many different -- many different sort of perspectives -- because we have an involvement obviously as a -- as a big company and a technology company; from helping clients with it, we have a whole business around; and then with influence and government regulation on this topic. But as I say to clients: Whatever you do on this topic, you don't do enough. That's it. Whatever you're doing, you don't do enough. And when you realize the level of sophistication in what it is we're talking about -- because it goes from being concerned about the theft of intellectual property to being concerned about economic, actually, harm to be done; to obviously nation-state sponsored sort of cybersecurity -- and then what you can do about it, actually this comes full circle. This becomes so complex, the best and, really, the way to deal with this, it is a big analytics problem -- is a big data analytics problem -- predictive. You'll never be able to know in advance every problem, and put a wall up for it. It's absolutely impossible. So the best you'll be able to do is use predictive analytics to look for things that look slightly, slightly, slightly out amiss, right? I always say, so you can see footprints in the sand beforehand. And so that is the idea around the analytics.
And then the regulation, which -- it is one area that -- regulation -- you can't regulate this -- it changes too fast. The most important thing you could do is -- as an example, what's in the House bill, which is have information sharing but without liability, right? The best thing is to be able to share information quickly between companies and government, without liability issues on it.
HAASS: But isn't one of your biggest issues is going to be here that this is obviously global, and even if we come up with some sharing and some rules of the road domestically, this is obviously the most global of activities? And the rules of the road -- I would say the gap between the technology and the international, political, legal, diplomatic framework is a chasm.
ROMETTY: Yeah, yeah. I would agree --
HAASS: And efforts so far to narrow it are not succeeding.
ROMETTY: I would agree. But the worst is the flip of that, is if every country tries to regulate this themselves, I mean, then you'll really have a complete standstill between -- and a greater vulnerability, right, at the end of the day.
HAASS: I've got two more questions. One is in terms of immigration and education reform.
Can I be -- you mentioned before you're getting some of the best Ph.D.s. A lot of the technology companies, when the CEOs or others are here, one of their first concerns is they can't get or if they get, they can't retain, people that -- the people they need. How important is comprehensive -- first of all, comprehensive immigration reform for a company like IBM --
ROMETTY: Oh, it's very -- it's very important. You would say the same thing. I think all of us -- I mean, this to me is -- the future for many, many companies are going to be folks that have math and science backgrounds and able to contribute in different ways. And so I think you would find that from many, many companies -- their inability to hire with the right skills, because even with unemployment, there are many job openings, right, if you had the right skill, to be filled.
So this issue about education is the root issue, right? So for jobs, part of the solving of a job is having the right skill to be able to fill it. And so, as you know -- something we were talking about this morning in a different session -- I feel very strongly there are things each of us in private sector can do about this topic, versus just talk about it and treat it as if it's a very large problem that's unsolvable. And there are a number in this room that we have done work together.
You had seen President Obama mentioned in his State of the Union address, he mentions a school that we had done in Brooklyn here called P-Tech. It's called Pathways to Technology. But it's something I think every business could participate and do. And in fact, others have joined us now. It's not -- it doesn't need to be us uniquely. And it took a high school and extended a six-year program. So two years of what we would call an Associate Degree here in the United States. And we influence the curriculum; we assign mentors. And then, these kids when they graduate, it's right of first refusal on a job.
Boy, their attendance has skyrocketed. We're into it a couple of years now and the kids, on average, already have 14 college credits so they're well on their way. Many will either graduate now early, we're finding, or are going to go on to university. And Rahm Emanuel started now five schools in Chicago. They're going to do -- Governor Cuomo said 10 more here.
So this would be -- in fact, in Chicago, we did this joining with -- Verizon joined us, Microsoft. There was a group of other companies that all then pitched in. Really, I believe we could solve a lot of this education in this same way in many places around the world -- in the country doing this, because you're training for the future skills in what companies need so they're employable.
So I've really got a lot of passion around this topic that we can all make a dent in this topic of both raising our folks here to have the right skill, makes this country more competitive, more productive. And in fact, solves a problem, as well as the skills you need.
HAASS: And what is your sense, for yourself, of here you are, you're a head of one of the major companies in the United States. You've got a workforce of nearly a half-a-million people. What is your sense of your either opportunity, obligation, responsibility -- choose your word -- as a corporate spokesperson, as a, if you will, a corporate statesman? What is your sense of what you're hoping to do with that part of your job?
ROMETTY: I think -- in general, or as relates to education? I mean --
HAASS: In general. Is education -- is education -- when you think of IBM, is education at the top, if you will, of the CSR kind of look?
ROMETTY: It is, but you know, it's an important point. And actually, to say CSR, I think the best thing for any company is when you can intersect your own business strategy with corporate social responsibility. And the reason I think many of us would all agree with that is it makes it sustainable. When they're dislocated, they're not sustainable. When they're intersected together, they are.
And so I think it's our obligation -- like I know many of the companies I see sitting here -- to play a big role, because just like I feel I'm the steward of this company from my period of time, it existed before and it will exist long after -- as long as we are very vigilant about transforming it. And in that same way, you play a role in being sure that you contribute to society, right? So you've got to contribute to society both from the cities, the education, the preparedness of what happens. And that's not just locally; that's on a global basis.
HAASS: Why don't I stop. Let's get some questions. If people would wait for a microphone and just give us your name and with whom and for whom you work, we will get as many questions in as we -- as we possibly can. We have a microphone somewhere running around the room.
Yes, sir. I see in the -- right there.
I apologize if I don't know everyone's name, but there's 170-or-so member companies and I ain't that good.
ROMETTY: Come on, you know them all. (Chuckles.)
QUESTIONER: OK, good. Well, I'm Jonathan Berman and I'm with Dalberg Global Advisors.
Just before I ask Ginni a question, I want to thank Richard for your proactive approach the cybersecurity issues here, both in terms of what you've done in terms of the program, but then also how you responded to your own challenge. I thought it was really impressive.
HAASS: Well, thank you. But there's no interest like self-interest. (Laughter.)
QUESTIONER: OK. And Virginia, I wanted to ask: IMB recently opened a research center in Nairobi -- one of only, I think, a dozen around the world.
QUESTIONER: Not every company would think to go to Nairobi. Why don't you talk a little bit about why you made that choice and why that works for IBM?
ROMETTY: Yeah, this is a -- this is a -- thank you for the question. And so IBM research -- and IBM spends on research and development about $6.5 billion a year. But in research, there are 12 centers around the world. The last three we've opened in the last year or so.
And so originally when research was built in IBM, you did what most research company -- or what most organizations who were going to set up research at the time did. You would have opened a center next to a very prestigious university -- be that MIT, be it Stanford, a whole list of them -- therefore, you'd get really smart people out of the university to come into your research organization.
Back to this issue about big data and the kind of problems in the world and urbanization, you no longer -- if you really want to work on the most pressing problems in the world, you're going to have to open up a research center in the middle of the problems. You can't bring the problems. They're too big. You can't bring the problem to research. You have to go immerse research in the middle of the problem, and that is how -- what took us to Nairobi. And have a government very anxious and interested and a population that wants to learn on top of it.
And I think what we may be able to do -- one of my hopes and aspirations for in Nairobi -- and I'll come back to Africa in a second -- is that you'll be able to -- if I may use the words -- you know, you're going to have good enough solutions come out of this. You know, necessity is the motherhood of invention. And we worked on -- it's a quick example: We worked on traffic congestion there; sent in a bunch of researchers. Well, had this been Brisbane, Stockholm, London, Sao Paulo -- any other city -- it would have been about massive infrastructure that would have to be put in place, all these cameras, all this information, systems to be built, log time, a tax referendum. Well, they had nine cameras. So nine low-grade cameras; that's it, but the researchers -- back to data and analytics -- said, you know what? Let us just take what you've got there. I think we could actually predict where traffic's going to go. Based on all different things, we can predict where every individual kind of car is going to go. And out of that came, you know, sure enough, close enough.
And so it's an example of -- you get an entirely different solution to come out of that. And I think that's what's going to happen. So that's how we picked Nairobi. And because a belief -- very strong belief -- that I hope the time is going to be in this next decade here that the time is right that Africa will. And when I say "Africa" -- those of you know the continent well -- it's 54 countries, so you can't paint it with one brush by any stretch. But we're in 24 countries today, and sub-Saharan Africa, in particular, great opportunity.
And as, you know, we'll see as these elections go and wrap one way or the other here, if we begin to see a dislocation between the political landscape and the business landscape, they can sort of not kind of go with one another, but maybe in a good way, be able to have some stability. And one is one of changes, as an example, that this is the time. So I believe strongly that this is the time. But it's a difficult place to build up resource, but having that there to solve some of these most important problems is why we opened up Nairobi.
HAASS: A lot of your colleagues in the community speak about other reasons for investing in places like Nairobi. They talk about opportunities abroad. The other reason, though, is what they see as barriers to investing here at home -- whether tax policy to questions about the political environment and so forth. To what extent is IBM, like a lot of other countries, holding off building capacity in the United States, because of concerns about the political economic environment here?
ROMETTY: Yeah. No, we've invested where it was the right place to invest right now. But that doesn't mean -- so I can't say that we have held off any investment and moved it differently because of that. But into the future, I would be the first one to stand up and say, you've got to have a competitive worldwide tax system for the United States, which includes not only rate, but it includes the ability to take that money and put it where you need to. And as I often describe, look, 80 percent of the opportunity is outside of the United States from a growth perspective. Eighty percent of the growth -- that's true across industries; it's just a fact -- 75 (percent) to 80 percent. And therefore, you're going to have to have and get resource to where that opportunity is.
At the same time, many of us have very -- quite a few very high-value and important jobs here in the United States, right? So you've got to have that ability to move your capital around. And when you do get to have to build something very capital intensive, you're going to have the ability to have to move the capital to where you want to build it. But to date, we've been governed by what is the right place to put it.
HAASS: Yes, ma'am?
QUESTIONER: Hi. My name is Ann Nicocelli with MetLife. Thank you so much for your comments.
As you know, the U.S. and many countries around the world are negotiating free-trade agreements rapidly. And within those free-trade agreements, you have provisions on cross-border data transfer.
QUESTIONER: I was wondering if you could characterize how you think countries are doing in general in setting up a framework for cross-border data transfer, as well as data privacy.
ROMETTY: Yeah, well, it's a little bit related, as well, to the security question as well.
Still, how are they doing? How would you rate it? There is much more work to be done on this, right? And so I think it's still at a stage where we've all got to still continue to advocate for these positions and advocate for the -- you can, in fact, have this state of sharing. And I mean, it transcends into the security topic, but it also transcends into things like indigenous innovation where people say, no, no, you've got to make it here, though. And you know, that to me -- whenever you try to restrict something from naturally going where it would for economic reasons, for skill reasons, for a good legal environment that it can exist in, you know, you're going to create a problem for the long run.
So I really believe those are the things that we've got to continue. I know every time I'm in a country and with the government, those are things -- one of the very top of the list topics to continue to advocate, because it's not where it needs to be.
HAASS: Andrew, up against the wall.
QUESTIONER: My name is Andrew Gundloch, First Eagle Investment Management.
I totally share your vision in terms of big data. And I'm curious why you see customers or companies failing to make the transition or failing to lead the transition in their industry to big data -- a big data world. Is it culture; is it organization?
You mentioned in the beginning the Obama campaign. It's interesting, because the Obama campaign led on big data and technology for two elections in a row. They won with my.obama.com (sic/my.barackobama.com) that Chris Hughes -- I don't know if he's here tonight -- built, and then on the data analysis for the second one.
But if you take another example, Major League Baseball, Billy Beane's -- or Michael Lewis's book came out and 10 years later, all that data is commoditized and competitive advantage has gone back to the traditional competitive advantage, which is money and big markets. So I'm curious why you see companies making it and not.
ROMETTY: Yeah. Back to, you know, some of the comments that I made, there's lots of reasons --
HAASS: Do you think the Yankees are too old this year to win? (Laughter.)
ROMETTY: No comment! (Laughter.)
So I think the biggest actual issue is culture. And this is -- cultural. And it's hard work. You know, I know from myself, because look, you get a couple different dynamics that happen: When people think of the word "big data," they sometimes think of that as a buzz word. And they say, of course I do data and of course I do analytics. And I can guarantee you, all of us do. Absolutely we do. Our businesses wouldn't be where they are.
This is about degrees of difference and precision and prediction. And you start to -- and using information. It's not just regular -- this will be one day videos, image, conversation. See, what you're not -- the kind of big data I'm thinking about -- if you had a picture of a graph and you kind of had a -- we've shown this. Kind of you are right here today. By 2015, the amount of information, it's going to be like this. You are at the 15 percent mark of what in three years is going to be flooding on you. And the majority of that isn't text. It is going to be information that's unstructured -- video image conversation, et cetera -- and it's going to be uncertain, meaning, what did that actually mean? Or one of my favorite examples was I can remember reading an article -- must have -- I'm pretty sure it was The New York Times -- it was talking about garbage trucks and that were they or were they not sitting in the Hudson River and should you dispatch emergency? What do you do? Were these GPS signals gone awry or were they actually there? And this is uncertain data; this is going to happen and you're going to make decisions real time on this.
And so that is a different world than the world of the past. So when I say this isn't the old world, it's going to be a huge tsunami of information. And then you're going to have to change processes, systems. I mean, just think: Because someone has, enabled by a device, they're able to order something right here. That means you're going to have to be sure your whole -- all your systems through the backend respond immediately to that.
I had a great example of a client who did work in retail. And they allowed all of their retail -- they were a store, a department store -- they had their customers, responding to the millennial generation, could create their own storefront, populate it with their material -- their, you know, different products out of the mother ship, as you might say, and then they would get a little commission. But if you know how the millennial generation works, they'll believe their friends more than they will anything else, so this is a good thing. It is a great thing. However, all of a sudden, you're not doing any planning anymore. You don't have insight into what's going to be required, what the demand's going -- it's coming through another way.
So this all ends up to be good, heavy-lifting hard work is the end of the story. So it's both culture and it's the ability to turn this into real business. You have to change real processes and real information. And so I think it's hard. That's kind of a short answer to it's hard. So it's both culture and hard, but that's why the basis for competitive advantage, those who do it, it does really differentiate you.
And by the way, one more point on this is that I don't care what business you're in, as you look into the future -- and everywhere I go in the world, every client I meet with, you'll have a discussion. And everyone, of course, talks about politics and the economy, but it's both growth and productivity. And even if you're in a growth market, you deal with productivity. And this data will be an answer to that productivity, because productivity does not have to mean cost cutting. And there'll be a point it can't be. It is all about, how do you make things more productive? And this will, in large part -- the use of this -- will help you with that piece.
HAASS: Ginni, before I call on Rik Kirkland, you've used the world "culture" several times. How do you recognize it and then how do you go about changing it?
ROMETTY: To me, I learned along the way, you know, culture is behavior. That's all it is; culture is people's behaviors. As someone once said to me, culture is what people do when no one looks, all right? And so it is true behaviors. And so what you have to do to change it -- I mean, and I think in most companies, the biggest and most important thing you can do is you have a set of values in a company. And instead of stopping there, you have to operationalize them. So people know, what are the behaviors expected of me? And I don't mean a rulebook. It's what do you do when there's no rule and you have to decide something? That's what a behavior and a value drives. So that's how you can operationalize it in a big group and it is just behaviors, right? So when I say "just behavior," but it's behaviors driven by values.
HAASS: And just -- does IBM, do you believe, have a culture that truly differentiates it from other companies, either in their technology space or more broadly?
ROMETTY: I do; I do, without a doubt. It's one of the few companies in the world -- and I'd be interested, whenever you think of your own firm, what do you call people that work there?
HAASS: Lucky. (Laughter.)
ROMETTY: OK. (Chuckles.) That was a very good answer, Richard.
Ours are -- what have you ever heard an IBM person called? Does anyone -- they're called IBM'ers. And it's -- to me it speaks to that culture that is a very unique culture. You are an IBM'er. And I hope our values -- look, every day I want and aspire to that, that the folks all walk and live those values, which are, of course, dedication to every client's success, innovation that matters for our company and the world, and trust in all personal responsibility.
So you know, those -- so does that make it unique? I think it does make it unique.
HAASS: Nice. Rik Kirkland.
QUESTIONER: Rik Kirkland from McKinsey.
I want to hear more about Watson. Watson is no longer the world's most famous game-playing computer; you put him to work. So what are you learning from his -- or its --
ROMETTY: Her -- her work?
QUESTIONER: Exactly -- her. What are you learning from her early experiences in the workplace? And maybe more important, given your remarks about the third era and computers learning, what is Watson learning?
ROMETTY: Yeah. So this is a great --
QUESTIONER: And where does that go?
ROMETTY: This is one of those -- when Richard says to me, when people would come here -- this is one, I hope, will be one of the greatest contributions that IBM will make in the future. So Watson -- did any -- many people see this on television when it played "Jeopardy?" Only the front row? Watson was a machine that played "Jeopardy." It is not -- it is not a search machine on -- you know, a big, giant search machine. That is not what it is.
What made it unique -- it is a machine that you do not program. It learns. It had, at the time, ingested millions of documents and it understands natural language, free format. So you speak to it and it will decide what you meant. And I think one of my favorite "Jeopardy" questions -- well, not my favorite, but it was a "Jeopardy" question -- when it asked it a question about a "chick," and it was actually speaking about a young girl, not a little bird. It had to be able to decipher the context -- what is that word mean?
HAASS: I hope Watson was generally offended at that. (Laughter.)
ROMETTY: Oh, well, it did learn something. You know, this is another longer story for over cocktails over what did it learn and, you know, big discussion: should you not teach it those bad things and unteach it those things? So it -- so one of the -- what has it done in the last two years since then?
So this was a grand challenge, because, you know, the team had to sign up to go compete on "Jeopardy" well before the machine was done, right? So talk about being under the gun with a TV contract, you know? OK, better get it going. And so they did; it won. So but that was just a beginning.
So the team has been commercializing it. And as I always say, it's been in medical school. So we could have chosen something different, but the first and biggest thing we did was assign it to work on oncology, and particularly some of the non-blood oncology. And those of you that may, for unfortunate reasons, be familiar with cancer, know that many times, the most important thing is first diagnosis and first treatment, which has a very large impact in the determination of the outcome.
So it has been, I mentioned earlier, working with Memorial Sloan-Kettering, the cancer center here; MD Anderson; Cleveland Clinic -- being taught by tens of the world's most renowned doctors. It has now ingested 2 (million) to 3 million different documents; 42 publications in their entirety, in their whole life; 600,000 medical evidence cases. And it is being trained to do two things: an adviser to a doctor to help with what is the correct treatment -- diagnosis and treatment, so as a treatment adviser. And then work with WellPoint, it's being used to help with when your tests are ordered. When you go to your doctor and the doctor has to go to your insurance company for authorization of utilization, what are the right protocols for different kinds of sicknesses and diseases?
So it's in -- already in pilot. Those two products have been in their first announcement. Its next thing it's working on -- so on one hand, we took one of the toughest things in the world and still lots to do, but a lot of progress on this. Now I go -- oh, by the way, one other thing: I watch when doctors interact with it. What it is -- and this is where you get to this cognitive -- you almost look as if it's a conversation between two colleagues, because what it answers back to the doctor is, well, here are the three options. Here's my confidence level and here's all the of the reasons why in the documentation I believe that to be true or false. And if I knew these things, I might have a different opinion. And so it's an iterative back and forth.
OK. Now we go to the other side of the world where we said, OK, now we don't have to always work on solving world hunger here. Can we do something a little easier? And we've been working with financial services and telcos on call centers. So talk about another whole different end of a spectrum. But as an example, big, big numbers speaking: In the call centers in the world, a typical call center, the operator or adviser you speak to spend 60 percent of their time trying to find the information to answer your question -- looking for documentation. And in the pilots we've done, they're able to cut this in half and more by -- because of its ability to have ingested and seen so much and instantly recall and associate things. And again, in English. Now, it's learning -- it's got to learn other languages too, but as an example, in medicine, the majority of the documentation in the world, regardless, is in English.
So both -- it's in medical school and it will soon pass the medical boards. It's in medical school and it's as well on the other side working in -- being in any job that needs an adviser. Because you know, I go back to medicine. The issue is the proliferation of information. There's no doctor that can read all of that and keep current.
And just think -- back to the question on Nairobi or Africa or India or China, all the places in the world, as well as places in the United States -- you know, if you could get gold-standard care without having to go, you will have an entirely different medical model, right? And so the numbers are something like 15 to 20 percent of people with cancer will ever really be treated by a cancer center in this country. They'll go to their local hospitals. And so this would be a way to dramatically influence those outcomes.
HAASS: Jacob Frenkel.
HAASS: Right up here -- second row.
QUESTIONER: (Off mic.)
HAASS: We can play "pass the microphone."
QUESTIONER: Thank you. Jacob Frenkel, JPMorgan.
You spoke about the opportunities, Africa and social responsibility. Let's try to combine them.
Demographers tell us that in the next 20 years, Africa will have more than half-a-billion added population -- more than all the additions to China, India together, et cetera. By the same token, these opportunities may not be there if the health situation is not going to be taken care of. So it is really an issue which is not just social responsibility, it's almost business interest.
ROMETTY: I agree.
QUESTIONER: How does a large company like IBM or others -- how do we translate that business interest, in addition to the human interest, to deal with that issue?
ROMETTY: Jacob that is -- I think not only is that a great question, it's a great statement of what it is: an obligation of many great companies to do. And so, you know, one method we picked to address that -- and it's actually -- I've got tell you, it's had a byproduct of being one of the best leadership development things we could have ever done to help IBM'ers become global citizens.
We started something called the Corporate Services Corps, OK, modeled on the Peace Corps idea. And by the way, we've done almost a hundred teams in Africa. And many of them -- infant mortality, cleanliness of water, all of these very related to the topics you're talking about in these parts of the world. And they are multidisciplinary teams from all -- I mean, they could be an accountant, a salesperson, a developer, a finance person, you name it, all coming -- a consultant -- come together. And then they go and they don't leave their day jobs, but they intersperse this with doing a lot of homework ahead of time. And then they go to a city. It could be a city; it could be a hospital; it could be a not-for-profit; it could be an organization. And they go spend months working on the problem. They did some great work in Nigeria, as an example, on infant mortality in a certain region and what to go do about it. Or food safety -- that's another big one -- about tracking and tracing of food and what happens to it. So there've been -- we've done one hundred of these projects across Europe now.
And I think that's both our privilege and obligation, given who we are, to do that. And it does -- look, back to this intersection of business and corporate social responsibility: So do we contribute? Absolutely. Do our people, though? It turns out they will tell you it's the number one most rewarding thing in their careers they have ever participated in. And now we have other companies -- we've said, you know, no reason we have to go just IBM'ers -- come along. And so we've got groups coming, you know -- and that's even better for folks. Now it's multi-companies going together on these teams -- back and forth, back and forth -- and with social technologies and like, they get a lot done away, as when they're there. They work on policy issues, as well as the solution issues. They continue on. Some of these have led to World Bank proposals and the like of what to go do afterwards and how to bring it to light. I think it's a real, like I say, privilege and obligation to work on these issues, because otherwise, it won't be good for any of us at the end of the day.
HAASS: We have a principle here and a tradition --
ROMETTY: On time!
HAASS: -- that's grown up over the last 60 years of corporate meetings is that we tend to begin and end on time. And there's also a reception to go to. I never like standing between several hundred people and a reception. But there's also an elephant in the room which I feel at least I've got to address. So one last question, if you'll forgive me, which is since you've been CEO, has your golf handicap gone up or down? (Laughter.)
ROMETTY: Oh, I am working, working, working all the time.
HAASS: That's a good sign. As a rule, you always want to invest in companies where the handicap is going up.
ROMETTY: This is -- I don't know if it's allowed to go higher; I don't know. (Laughter.)
HAASS: Anyhow, Ginni, thank you for tonight. And thank you -- (applause).
ROMETTY: Thank you. My pleasure -- with pleasure. Good fun. (Applause.)