0:00:01.063,0:00:02.578 There's an old joke about a cop 0:00:02.602,0:00:04.959 who's walking his beat[br]in the middle of the night, 0:00:04.983,0:00:07.086 and he comes across a guy[br]under a street lamp 0:00:07.110,0:00:09.801 who's looking at the ground[br]and moving from side to side, 0:00:09.825,0:00:11.602 and the cop asks him what he's doing. 0:00:11.626,0:00:13.560 The guys says he's looking for his keys. 0:00:13.584,0:00:15.023 So the cop takes his time 0:00:15.047,0:00:17.317 and looks over and kind of[br]makes a little matrix 0:00:17.341,0:00:19.546 and looks for about two, three minutes. 0:00:19.570,0:00:20.721 No keys. 0:00:20.745,0:00:23.117 The cop says, "Are you sure? 0:00:23.141,0:00:25.450 Hey buddy, are you sure[br]you lost your keys here?" 0:00:25.474,0:00:27.506 And the guy says,[br]"No, actually I lost them 0:00:27.530,0:00:29.256 down at the other end of the street, 0:00:29.280,0:00:30.725 but the light is better here." 0:00:30.749,0:00:33.374 (Laughter) 0:00:34.167,0:00:37.410 There's a concept that people talk[br]about nowadays called "big data." 0:00:37.434,0:00:40.077 And what they're talking[br]about is all of the information 0:00:40.101,0:00:42.252 that we're generating[br]through our interaction 0:00:42.276,0:00:43.579 with and over the Internet, 0:00:43.603,0:00:45.363 everything from Facebook and Twitter 0:00:45.387,0:00:49.020 to music downloads, movies,[br]streaming, all this kind of stuff, 0:00:49.044,0:00:50.506 the live streaming of TED. 0:00:50.919,0:00:53.603 And the folks who work[br]with big data, for them, 0:00:53.627,0:00:55.631 they talk about that their biggest problem 0:00:55.655,0:00:57.402 is we have so much information. 0:00:57.426,0:01:00.803 The biggest problem is: how do we[br]organize all that information? 0:01:01.272,0:01:03.432 I can tell you that,[br]working in global health, 0:01:03.456,0:01:05.740 that is not our biggest problem. 0:01:06.232,0:01:09.416 Because for us, even though[br]the light is better on the Internet, 0:01:10.989,0:01:14.355 the data that would help us solve[br]the problems we're trying to solve 0:01:14.379,0:01:16.528 is not actually present on the Internet. 0:01:16.552,0:01:17.997 So we don't know, for example, 0:01:18.021,0:01:21.312 how many people right now[br]are being affected by disasters 0:01:21.336,0:01:23.305 or by conflict situations. 0:01:23.329,0:01:27.048 We don't know for, really,[br]basically, any of the clinics 0:01:27.072,0:01:28.222 in the developing world, 0:01:28.246,0:01:30.701 which ones have medicines[br]and which ones don't. 0:01:30.725,0:01:34.099 We have no idea of what[br]the supply chain is for those clinics. 0:01:34.123,0:01:37.821 We don't know -- and this is really[br]amazing to me -- we don't know 0:01:37.845,0:01:41.615 how many children were born --[br]or how many children there are -- 0:01:41.639,0:01:45.047 in Bolivia or Botswana or Bhutan. 0:01:46.047,0:01:48.088 We don't know how many kids died last week 0:01:48.112,0:01:49.358 in any of those countries. 0:01:49.382,0:01:52.429 We don't know the needs[br]of the elderly, the mentally ill. 0:01:52.453,0:01:55.668 For all of these different[br]critically important problems 0:01:55.692,0:01:58.992 or critically important areas[br]that we want to solve problems in, 0:01:59.016,0:02:01.282 we basically know nothing at all. 0:02:03.834,0:02:06.486 And part of the reason[br]why we don't know anything at all 0:02:06.510,0:02:10.689 is that the information technology systems[br]that we use in global health 0:02:10.713,0:02:15.126 to find the data to solve[br]these problems is what you see here. 0:02:15.150,0:02:17.384 This is about a 5,000-year-old technology. 0:02:17.408,0:02:19.140 Some of you may have used it before. 0:02:19.164,0:02:20.703 It's kind of on its way out now, 0:02:20.727,0:02:23.166 but we still use it[br]for 99 percent of our stuff. 0:02:23.190,0:02:25.680 This is a paper form. 0:02:26.010,0:02:28.043 And what you're looking at is a paper form 0:02:28.067,0:02:31.246 in the hand of a Ministry of Health[br]nurse in Indonesia, 0:02:31.270,0:02:33.510 who is tramping out across the countryside 0:02:33.534,0:02:37.185 in Indonesia on, I'm sure,[br]a very hot and humid day, 0:02:37.209,0:02:39.891 and she is going to be knocking[br]on thousands of doors 0:02:39.915,0:02:41.994 over a period of weeks or months, 0:02:42.018,0:02:43.615 knocking on the doors and saying, 0:02:43.639,0:02:46.517 "Excuse me, we'd like to ask[br]you some questions. 0:02:46.541,0:02:49.746 Do you have any children?[br]Were your children vaccinated?" 0:02:50.223,0:02:52.358 Because the only way[br]we can actually find out 0:02:52.382,0:02:55.317 how many children were vaccinated[br]in the country of Indonesia, 0:02:55.341,0:02:56.898 what percentage were vaccinated, 0:02:56.922,0:03:01.050 is actually not on the Internet,[br]but by going out and knocking on doors, 0:03:01.074,0:03:03.288 sometimes tens of thousands of doors. 0:03:03.312,0:03:07.310 Sometimes it takes months to even years[br]to do something like this. 0:03:07.334,0:03:09.451 You know, a census of Indonesia 0:03:09.475,0:03:11.569 would probably take[br]two years to accomplish. 0:03:11.593,0:03:13.665 And the problem, of course,[br]with all of this 0:03:13.689,0:03:15.586 is that, with all those paper forms -- 0:03:15.610,0:03:18.729 and I'm telling you, we have[br]paper forms for every possible thing: 0:03:18.753,0:03:20.817 We have paper forms[br]for vaccination surveys. 0:03:20.841,0:03:24.002 We have paper forms to track[br]people who come into clinics. 0:03:24.026,0:03:28.068 We have paper forms to track[br]drug supplies, blood supplies -- 0:03:28.092,0:03:31.326 all these different paper forms[br]for many different topics, 0:03:31.350,0:03:33.666 they all have a single, common endpoint, 0:03:33.690,0:03:36.309 and the common endpoint[br]looks something like this. 0:03:36.333,0:03:39.666 And what we're looking[br]at here is a truckful of data. 0:03:41.261,0:03:45.126 This is the data from a single[br]vaccination coverage survey 0:03:45.150,0:03:47.341 in a single district[br]in the country of Zambia 0:03:47.365,0:03:49.655 from a few years ago,[br]that I participated in. 0:03:49.679,0:03:52.026 The only thing anyone[br]was trying to find out 0:03:52.050,0:03:55.303 is what percentage of Zambian[br]children are vaccinated, 0:03:55.327,0:03:58.581 and this is the data,[br]collected on paper over weeks, 0:03:58.605,0:03:59.788 from a single district, 0:03:59.812,0:04:02.487 which is something like a county[br]in the United States. 0:04:02.511,0:04:05.186 You can imagine that,[br]for the entire country of Zambia, 0:04:05.210,0:04:07.503 answering just that single question ... 0:04:08.615,0:04:09.945 looks something like this. 0:04:11.072,0:04:13.112 Truck after truck after truck, 0:04:13.136,0:04:16.049 filled with stack after stack[br]after stack of data. 0:04:16.430,0:04:19.642 And what makes it even worse[br]is that's just the beginning. 0:04:19.666,0:04:21.760 Because once you've collected[br]all that data, 0:04:21.784,0:04:24.324 of course, someone --[br]some unfortunate person -- 0:04:24.348,0:04:26.563 is going to have to type that[br]into a computer. 0:04:26.587,0:04:28.039 When I was a graduate student, 0:04:28.063,0:04:30.522 I actually was that unfortunate[br]person sometimes. 0:04:30.546,0:04:33.561 I can tell you, I often wasn't[br]really paying attention. 0:04:33.585,0:04:35.852 I probably made a lot[br]of mistakes when I did it 0:04:35.876,0:04:38.496 that no one ever discovered,[br]so data quality goes down. 0:04:38.520,0:04:41.540 But eventually that data, hopefully,[br]gets typed into a computer, 0:04:41.564,0:04:43.295 and someone can begin to analyze it, 0:04:43.319,0:04:46.191 and once they have[br]an analysis and a report, 0:04:46.215,0:04:49.239 hopefully, then you can take[br]the results of that data collection 0:04:49.263,0:04:51.230 and use it to vaccinate children better. 0:04:51.254,0:04:56.795 Because if there's anything worse[br]in the field of global public health -- 0:04:56.819,0:04:59.801 I don't know what's worse[br]than allowing children on this planet 0:04:59.825,0:05:01.941 to die of vaccine-preventable diseases -- 0:05:02.679,0:05:05.377 diseases for which[br]the vaccine costs a dollar. 0:05:05.835,0:05:09.187 And millions of children die[br]of these diseases every year. 0:05:09.211,0:05:12.185 And the fact is, millions[br]is a gross estimate, 0:05:12.209,0:05:15.423 because we don't really know[br]how many kids die each year of this. 0:05:15.730,0:05:19.229 What makes it even more frustrating[br]is that the data-entry part, 0:05:19.253,0:05:21.443 the part that I used to do[br]as a grad student, 0:05:21.467,0:05:22.925 can take sometimes six months. 0:05:22.949,0:05:26.401 Sometimes it can take two years[br]to type that information into a computer, 0:05:26.425,0:05:28.535 And sometimes, actually not infrequently, 0:05:28.559,0:05:30.387 it actually never happens. 0:05:30.411,0:05:32.887 Now try and wrap your head[br]around that for a second. 0:05:32.911,0:05:35.086 You just had teams of hundreds of people. 0:05:35.110,0:05:38.013 They went out into the field[br]to answer a particular question. 0:05:38.037,0:05:40.433 You probably spent hundreds[br]of thousands of dollars 0:05:40.457,0:05:43.493 on fuel and photocopying and per diem. 0:05:44.072,0:05:46.116 And then for some reason, momentum is lost 0:05:46.140,0:05:47.533 or there's no money left, 0:05:47.557,0:05:49.894 and all of that comes to nothing, 0:05:49.918,0:05:52.641 because no one actually types it[br]into the computer at all. 0:05:52.665,0:05:53.841 The process just stops. 0:05:53.865,0:05:55.789 Happens all the time. 0:05:55.813,0:05:58.928 This is what we base[br]our decisions on in global health: 0:05:58.952,0:06:02.369 little data, old data, no data. 0:06:03.924,0:06:05.377 So back in 1995, 0:06:05.401,0:06:08.641 I began to think about ways[br]in which we could improve this process. 0:06:08.665,0:06:11.333 Now 1995 -- obviously,[br]that was quite a long time ago. 0:06:11.357,0:06:14.335 It kind of frightens me to think[br]of how long ago that was. 0:06:14.359,0:06:17.097 The top movie of the year[br]was "Die Hard with a Vengeance." 0:06:17.121,0:06:19.938 As you can see, Bruce Willis[br]had a lot more hair back then. 0:06:19.962,0:06:22.627 I was working in the Centers[br]for Disease Control 0:06:22.651,0:06:24.830 and I had a lot more[br]hair back then as well. 0:06:25.505,0:06:28.449 But to me, the most significant[br]thing that I saw in 1995 0:06:28.473,0:06:29.691 was this. 0:06:30.151,0:06:32.544 Hard for us to imagine, but in 1995, 0:06:32.568,0:06:35.683 this was the ultimate elite mobile device. 0:06:36.286,0:06:38.842 It wasn't an iPhone.[br]It wasn't a Galaxy phone. 0:06:38.866,0:06:40.230 It was a PalmPilot. 0:06:40.254,0:06:43.782 And when I saw the PalmPilot[br]for the first time, I thought, 0:06:43.806,0:06:46.203 "Why can't we put the forms[br]on these PalmPilots? 0:06:46.758,0:06:49.378 And go out into the field[br]just carrying one PalmPilot, 0:06:49.402,0:06:53.167 which can hold the capacity[br]of tens of thousands of paper forms? 0:06:53.191,0:06:54.618 Why don't we try to do that? 0:06:54.642,0:06:55.905 Because if we can do that, 0:06:55.929,0:06:59.738 if we can actually just collect[br]the data electronically, digitally, 0:06:59.762,0:07:01.419 from the very beginning, 0:07:01.443,0:07:04.719 we can just put a shortcut right[br]through that whole process 0:07:04.743,0:07:09.735 of typing, of having somebody type[br]that stuff into the computer. 0:07:09.759,0:07:11.599 We can skip straight to the analysis 0:07:11.623,0:07:14.762 and then straight to the use[br]of the data to actually save lives." 0:07:14.786,0:07:17.373 So that's what I began to do. 0:07:17.397,0:07:21.746 Working at CDC, I began to travel[br]to different programs around the world 0:07:21.770,0:07:25.912 and to train them in using[br]PalmPilots to do data collection, 0:07:25.936,0:07:27.314 instead of using paper. 0:07:27.338,0:07:29.226 And it actually worked great. 0:07:29.250,0:07:32.302 It worked exactly as well[br]as anybody would have predicted. 0:07:32.326,0:07:33.483 What do you know? 0:07:33.507,0:07:37.119 Digital data collection is actually[br]more efficient than collecting on paper. 0:07:37.143,0:07:39.175 While I was doing it, my business partner, 0:07:39.199,0:07:42.278 Rose, who's here with her husband,[br]Matthew, here in the audience, 0:07:42.302,0:07:45.175 Rose was out doing similar stuff[br]for the American Red Cross. 0:07:45.199,0:07:47.585 The problem was,[br]after a few years of doing that, 0:07:47.609,0:07:51.506 I realized -- I had been to maybe[br]six or seven programs -- 0:07:51.530,0:07:54.791 and I thought, you know,[br]if I keep this up at this pace, 0:07:54.815,0:07:55.966 over my whole career, 0:07:55.990,0:07:58.669 maybe I'm going to go[br]to maybe 20 or 30 programs. 0:07:58.693,0:08:01.836 But the problem is, 20 or 30 programs, 0:08:01.860,0:08:04.810 like, training 20 or 30 programs[br]to use this technology, 0:08:04.834,0:08:07.000 that is a tiny drop in the bucket. 0:08:07.024,0:08:10.964 The demand for this, the need[br]for data to run better programs 0:08:10.988,0:08:13.846 just within health -- not to mention[br]all of the other fields 0:08:13.870,0:08:15.866 in developing countries -- is enormous. 0:08:15.890,0:08:19.876 There are millions and millions[br]and millions of programs, 0:08:19.900,0:08:22.468 millions of clinics[br]that need to track drugs, 0:08:22.492,0:08:23.896 millions of vaccine programs. 0:08:23.920,0:08:26.181 There are schools[br]that need to track attendance. 0:08:26.205,0:08:30.111 There are all these different things[br]for us to get the data that we need to do. 0:08:30.135,0:08:34.754 And I realized if I kept up[br]the way that I was doing, 0:08:34.778,0:08:37.998 I was basically hardly[br]going to make any impact 0:08:38.022,0:08:39.375 by the end of my career. 0:08:39.756,0:08:41.624 And so I began to rack my brain, 0:08:41.648,0:08:44.592 trying to think about, what[br]was the process that I was doing? 0:08:44.616,0:08:45.898 How was I training folks, 0:08:45.922,0:08:49.096 and what were the bottlenecks[br]and what were the obstacles 0:08:49.120,0:08:51.815 to doing it faster[br]and to doing it more efficiently? 0:08:51.839,0:08:54.675 And, unfortunately, after thinking[br]about this for some time, 0:08:54.699,0:08:57.870 I identified the main obstacle. 0:08:58.475,0:09:00.396 And the main obstacle, it turned out -- 0:09:00.420,0:09:02.008 and this is a sad realization -- 0:09:02.032,0:09:03.745 the main obstacle was me. 0:09:04.229,0:09:05.658 So what do I mean by that? 0:09:06.538,0:09:08.254 I had developed a process 0:09:08.278,0:09:12.645 whereby I was the center[br]of the universe of this technology. 0:09:14.304,0:09:17.627 If you wanted to use this technology,[br]you had to get in touch with me. 0:09:17.651,0:09:19.475 That means you had to know I existed. 0:09:19.499,0:09:22.912 Then you had to find the money[br]to pay for me to fly out to your country 0:09:22.936,0:09:26.531 and the money to pay for my hotel[br]and my per diem and my daily rate. 0:09:26.555,0:09:29.554 So you could be talking[br]about 10- or 20- or 30,000 dollars, 0:09:29.578,0:09:31.872 if I actually had the time[br]or it fit my schedule 0:09:31.896,0:09:33.245 and I wasn't on vacation. 0:09:33.594,0:09:35.555 The point is that anything, 0:09:35.579,0:09:37.942 any system that depends[br]on a single human being 0:09:37.966,0:09:39.869 or two or three or five human beings -- 0:09:39.893,0:09:41.546 it just doesn't scale. 0:09:41.570,0:09:44.769 And this is a problem for which[br]we need to scale this technology, 0:09:44.793,0:09:46.363 and we need to scale it now. 0:09:46.387,0:09:49.141 And so I began to think of ways[br]in which I could basically 0:09:49.165,0:09:51.753 take myself out of the picture. 0:09:54.071,0:09:55.715 And, you know, I was thinking, 0:09:55.739,0:09:57.843 "How could I take myself[br]out of the picture?" 0:09:57.867,0:09:59.486 for quite some time. 0:09:59.510,0:10:02.986 I'd been trained that the way[br]you distribute technology 0:10:03.010,0:10:04.566 within international development 0:10:04.590,0:10:06.152 is always consultant-based. 0:10:06.176,0:10:09.177 It's always guys[br]that look pretty much like me, 0:10:09.201,0:10:11.749 flying from countries[br]that look pretty much like this 0:10:11.773,0:10:14.112 to other countries[br]with people with darker skin. 0:10:14.769,0:10:17.231 And you go out there,[br]and you spend money on airfare 0:10:17.255,0:10:20.491 and you spend time and you spend per diem 0:10:20.515,0:10:22.864 and you spend for a hotel[br]and all that stuff. 0:10:22.888,0:10:26.300 As far as I knew, that was the only way[br]you could distribute technology, 0:10:26.324,0:10:28.359 and I couldn't figure out a way around it. 0:10:28.383,0:10:30.137 But the miracle that happened -- 0:10:30.851,0:10:32.757 I'm going to call it Hotmail for short. 0:10:33.168,0:10:35.591 You may not think of Hotmail[br]as being miraculous, 0:10:35.615,0:10:37.052 but for me it was miraculous, 0:10:37.076,0:10:40.688 because I noticed, just as I[br]was wrestling with this problem -- 0:10:40.712,0:10:44.218 I was working in sub-Saharan[br]Africa, mostly, at the time -- 0:10:44.242,0:10:46.807 I noticed that every sub-Saharan[br]African health worker 0:10:46.831,0:10:49.775 that I was working with[br]had a Hotmail account. 0:10:51.389,0:10:54.317 And it struck me, "Wait a minute -- 0:10:54.341,0:10:58.579 I know the Hotmail people surely didn't[br]fly to the Ministry of Health in Kenya 0:10:58.603,0:11:00.679 to train people in how to use Hotmail. 0:11:01.382,0:11:05.630 So these guys are distributing technology,[br]getting software capacity out there, 0:11:05.654,0:11:07.982 but they're not actually[br]flying around the world. 0:11:08.006,0:11:09.578 I need to think about this more." 0:11:09.602,0:11:11.052 While I was thinking about it, 0:11:11.076,0:11:14.235 people started using even more[br]things like this, just as we were. 0:11:14.259,0:11:17.490 They started using LinkedIn and Flickr[br]and Gmail and Google Maps -- 0:11:17.514,0:11:18.671 all these things. 0:11:18.695,0:11:21.386 Of course, all of these things[br]are cloud based 0:11:21.410,0:11:23.559 and don't require any training. 0:11:23.583,0:11:25.259 They don't require any programmers. 0:11:25.283,0:11:26.786 They don't require consultants. 0:11:26.810,0:11:29.295 Because the business model[br]for all these businesses 0:11:29.319,0:11:32.256 requires that something be so simple[br]we can use it ourselves, 0:11:32.280,0:11:33.574 with little or no training. 0:11:33.598,0:11:36.193 You just have to hear about it[br]and go to the website. 0:11:36.217,0:11:40.413 And so I thought, what would happen[br]if we built software 0:11:40.437,0:11:42.501 to do what I'd been consulting in? 0:11:42.525,0:11:46.597 Instead of training people[br]how to put forms onto mobile devices, 0:11:46.621,0:11:49.922 let's create software that lets them[br]do it themselves with no training 0:11:49.946,0:11:51.382 and without me being involved. 0:11:51.406,0:11:52.890 And that's exactly what we did. 0:11:52.914,0:11:58.135 So we created software called Magpi,[br]which has an online form creator. 0:11:58.159,0:11:59.411 No one has to speak to me, 0:11:59.435,0:12:02.236 you just have to hear about it[br]and go to the website. 0:12:02.260,0:12:04.918 You can create forms,[br]and once you've created the forms, 0:12:04.942,0:12:07.403 you push them to a variety[br]of common mobile phones. 0:12:07.427,0:12:10.944 Obviously, nowadays, we've moved[br]past PalmPilots to mobile phones. 0:12:10.968,0:12:14.197 And it doesn't have to be a smartphone,[br]it can be a basic phone, 0:12:14.221,0:12:16.711 like the phone on the right,[br]the basic Symbian phone 0:12:16.735,0:12:18.797 that's very common[br]in developing countries. 0:12:18.821,0:12:22.510 And the great part about this[br]is it's just like Hotmail. 0:12:22.534,0:12:23.685 It's cloud based, 0:12:23.709,0:12:26.962 and it doesn't require any training,[br]programming, consultants. 0:12:26.986,0:12:29.189 But there are some[br]additional benefits as well. 0:12:29.213,0:12:31.086 Now we knew when we built this system, 0:12:31.110,0:12:33.665 the whole point of it,[br]just like with the PalmPilots, 0:12:33.689,0:12:36.488 was that you'd be able to collect the data 0:12:36.512,0:12:39.110 and immediately upload[br]the data and get your data set. 0:12:39.134,0:12:42.119 But what we found, of course,[br]since it's already on a computer, 0:12:42.143,0:12:44.754 we can deliver instant maps[br]and analysis and graphing. 0:12:44.778,0:12:46.849 We can take a process that took two years 0:12:46.873,0:12:49.881 and compress that[br]down to the space of five minutes. 0:12:50.222,0:12:52.377 Unbelievable improvements in efficiency. 0:12:52.740,0:12:56.448 Cloud based, no training,[br]no consultants, no me. 0:12:57.520,0:12:59.791 And I told you that in the first few years 0:12:59.815,0:13:01.884 of trying to do this[br]the old-fashioned way, 0:13:01.908,0:13:03.187 going out to each country, 0:13:03.211,0:13:07.432 we probably trained about 1,000 people. 0:13:07.871,0:13:09.553 What happened after we did this? 0:13:09.577,0:13:11.038 In the second three years, 0:13:11.062,0:13:13.212 we had 14,000 people find the website, 0:13:13.236,0:13:15.349 sign up and start using it[br]to collect data: 0:13:15.373,0:13:17.283 data for disaster response, 0:13:17.307,0:13:21.741 Canadian pig farmers[br]tracking pig disease and pig herds, 0:13:21.765,0:13:23.646 people tracking drug supplies. 0:13:24.241,0:13:27.585 One of my favorite examples, the IRC,[br]International Rescue Committee, 0:13:27.609,0:13:30.822 they have a program[br]where semi-literate midwives, 0:13:30.846,0:13:33.249 using $10 mobile phones, 0:13:33.273,0:13:36.574 send a text message[br]using our software, once a week, 0:13:36.598,0:13:39.074 with the number of births[br]and the number of deaths, 0:13:39.098,0:13:42.670 which gives IRC something that no one[br]in global health has ever had: 0:13:42.694,0:13:46.216 a near-real-time system[br]of counting babies, 0:13:46.240,0:13:47.874 of knowing how many kids are born, 0:13:47.898,0:13:50.540 of knowing how many children[br]there are in Sierra Leone, 0:13:50.564,0:13:52.787 which is the country[br]where this is happening, 0:13:52.811,0:13:54.564 and knowing how many children die. 0:13:55.394,0:13:56.967 Physicians for Human Rights -- 0:13:56.991,0:13:59.583 this is moving a little bit[br]outside the health field -- 0:13:59.607,0:14:04.390 they're basically training people[br]to do rape exams in Congo, 0:14:04.414,0:14:05.863 where this is an epidemic, 0:14:05.887,0:14:07.680 a horrible epidemic, 0:14:07.704,0:14:10.880 and they're using our software[br]to document the evidence they find, 0:14:10.904,0:14:12.878 including photographically, 0:14:12.902,0:14:15.805 so that they can bring[br]the perpetrators to justice. 0:14:16.956,0:14:20.549 Camfed, another charity[br]based out of the UK -- 0:14:20.573,0:14:23.286 Camfed pays girls' families[br]to keep them in school. 0:14:24.165,0:14:27.640 They understand this is the most[br]significant intervention they can make. 0:14:27.664,0:14:31.504 They used to track the disbursements,[br]the attendance, the grades, on paper. 0:14:31.528,0:14:34.875 The turnaround time between a teacher[br]writing down grades or attendance 0:14:34.899,0:14:37.734 and getting that into a report[br]was about two to three years. 0:14:37.758,0:14:38.909 Now it's real time. 0:14:38.933,0:14:42.116 And because this is such a low-cost[br]system and based in the cloud, 0:14:42.140,0:14:46.129 it costs, for the entire five countries[br]that Camfed runs this in, 0:14:46.153,0:14:48.018 with tens of thousands of girls, 0:14:48.042,0:14:50.750 the whole cost combined[br]is 10,000 dollars a year. 0:14:51.154,0:14:53.115 That's less than I used to get 0:14:53.139,0:14:56.035 just traveling out for two weeks[br]to do a consultation. 0:14:58.139,0:15:01.608 So I told you before that when[br]we were doing it the old-fashioned way, 0:15:01.632,0:15:05.427 I realized all of our work was really[br]adding up to just a drop in the bucket -- 0:15:05.451,0:15:07.173 10, 20, 30 different programs. 0:15:08.036,0:15:09.449 We've made a lot of progress, 0:15:09.473,0:15:11.029 but I recognize that right now, 0:15:11.053,0:15:14.417 even the work that we've done[br]with 14,000 people using this 0:15:14.441,0:15:15.904 is still a drop in the bucket. 0:15:15.928,0:15:18.658 But something's changed,[br]and I think it should be obvious. 0:15:18.682,0:15:20.837 What's changed now is, 0:15:20.861,0:15:24.163 instead of having a program[br]in which we're scaling at such a slow rate 0:15:24.187,0:15:27.498 that we can never reach[br]all the people who need us, 0:15:27.522,0:15:31.104 we've made it unnecessary[br]for people to get reached by us. 0:15:31.128,0:15:36.131 We've created a tool[br]that lets programs keep kids in school, 0:15:36.155,0:15:40.094 track the number of babies that are born[br]and the number of babies that die, 0:15:40.118,0:15:43.895 catch criminals and successfully[br]prosecute them -- 0:15:43.919,0:15:48.341 to do all these different things[br]to learn more about what's going on, 0:15:48.365,0:15:49.666 to understand more, 0:15:49.690,0:15:51.006 to see more ... 0:15:51.911,0:15:53.816 and to save lives and improve lives. 0:15:55.920,0:15:57.072 Thank you. 0:15:57.096,0:16:01.365 (Applause)