0:00:00.000,0:00:03.000
There's an old joke about a cop who's walking his beat

0:00:03.000,0:00:04.000
in the middle of the night,

0:00:04.000,0:00:06.000
and he comes across a guy under a street lamp

0:00:06.000,0:00:09.000
who's looking at the ground and moving from side to side,

0:00:09.000,0:00:11.000
and the cop asks him what he's doing.

0:00:11.000,0:00:13.000
The guys says he's looking for his keys.

0:00:13.000,0:00:15.000
So the cop takes his time and looks over

0:00:15.000,0:00:17.000
and kind of makes a little matrix and looks

0:00:17.000,0:00:20.000
for about two, three minutes. No keys.

0:00:20.000,0:00:23.000
The cop says, "Are you sure? Hey buddy,

0:00:23.000,0:00:25.000
are you sure you lost your keys here?"

0:00:25.000,0:00:26.000
And the guy says, "No, no, actually I lost them

0:00:26.000,0:00:28.000
down at the other end of the street,

0:00:28.000,0:00:34.000
but the light is better here."

0:00:34.000,0:00:35.000
There's a concept that people talk about nowadays

0:00:35.000,0:00:38.000
called big data, and what they're talking about

0:00:38.000,0:00:40.000
is all of the information that we're generating

0:00:40.000,0:00:43.000
through our interaction with and over the Internet,

0:00:43.000,0:00:44.000
everything from Facebook and Twitter

0:00:44.000,0:00:49.000
to music downloads, movies, streaming, all this kind of stuff,

0:00:49.000,0:00:50.000
the live streaming of TED.

0:00:50.000,0:00:53.000
And the folks who work with big data, for them,

0:00:53.000,0:00:55.000
they talk about that their biggest problem is

0:00:55.000,0:00:57.000
we have so much information,

0:00:57.000,0:01:00.000
the biggest problem is, how do we organize all that information?

0:01:00.000,0:01:03.000
I can tell you that working in global health,

0:01:03.000,0:01:06.000
that is not our biggest problem.

0:01:06.000,0:01:07.000
Because for us, even though the light

0:01:07.000,0:01:10.000
is better on the Internet,

0:01:10.000,0:01:13.000
the data that would help us solve the problems

0:01:13.000,0:01:16.000
we're trying to solve is not actually present on the Internet.

0:01:16.000,0:01:18.000
So we don't know, for example, how many people

0:01:18.000,0:01:20.000
right now are being affected by disasters

0:01:20.000,0:01:23.000
or by conflict situations.

0:01:23.000,0:01:27.000
We don't know for really basically any of the clinics

0:01:27.000,0:01:29.000
in the developing world, which ones have medicines

0:01:29.000,0:01:30.000
and which ones don't.

0:01:30.000,0:01:33.000
We have no idea of what the supply chain is for those clinics.

0:01:33.000,0:01:36.000
We don't know -- and this is really amazing to me --

0:01:36.000,0:01:39.000
we don't know how many children were born,

0:01:39.000,0:01:42.000
or how many children there are in Bolivia

0:01:42.000,0:01:45.000
or Botswana or Bhutan.

0:01:45.000,0:01:47.000
We don't know how many kids died last week

0:01:47.000,0:01:49.000
in any of those countries.

0:01:49.000,0:01:52.000
We don't know the needs of the elderly, the mentally ill.

0:01:52.000,0:01:55.000
For all of these different critically important problems

0:01:55.000,0:01:58.000
or critically important areas that we want to solve problems in,

0:01:58.000,0:02:03.000
we basically know nothing at all.

0:02:03.000,0:02:06.000
And part of the reason why we don't know anything at all

0:02:06.000,0:02:08.000
is that the information technology systems

0:02:08.000,0:02:12.000
that we use in global health to find the data

0:02:12.000,0:02:15.000
to solve these problems is what you see here.

0:02:15.000,0:02:17.000
And this is about a 5,000-year-old technology.

0:02:17.000,0:02:18.000
Some of you may have used it before.

0:02:18.000,0:02:20.000
It's kind of on its way out now, but we still use it

0:02:20.000,0:02:22.000
for 99 percent of our stuff.

0:02:22.000,0:02:26.000
This is a paper form, and what you're looking at

0:02:26.000,0:02:30.000
is a paper form in the hand of a Ministry of Health nurse

0:02:30.000,0:02:33.000
in Indonesia who is tramping out across the countryside

0:02:33.000,0:02:37.000
in Indonesia on, I'm sure, a very hot and humid day,

0:02:37.000,0:02:39.000
and she is going to be knocking on thousands of doors

0:02:39.000,0:02:41.000
over a period of weeks or months,

0:02:41.000,0:02:44.000
knocking on the doors and saying, "Excuse me,

0:02:44.000,0:02:46.000
we'd like to ask you some questions.

0:02:46.000,0:02:50.000
Do you have any children? Were your children vaccinated?"

0:02:50.000,0:02:51.000
Because the only way we can actually find out

0:02:51.000,0:02:54.000
how many children were vaccinated in the country of Indonesia,

0:02:54.000,0:02:57.000
what percentage were vaccinated, is actually not

0:02:57.000,0:03:00.000
on the Internet but by going out and knocking on doors,

0:03:00.000,0:03:03.000
sometimes tens of thousands of doors.

0:03:03.000,0:03:05.000
Sometimes it takes months to even years

0:03:05.000,0:03:07.000
to do something like this.

0:03:07.000,0:03:09.000
You know, a census of Indonesia

0:03:09.000,0:03:11.000
would probably take two years to accomplish.

0:03:11.000,0:03:13.000
And the problem, of course, with all of this is that

0:03:13.000,0:03:15.000
with all those paper forms — and I'm telling you

0:03:15.000,0:03:17.000
we have paper forms for every possible thing.

0:03:17.000,0:03:20.000
We have paper forms for vaccination surveys.

0:03:20.000,0:03:24.000
We have paper forms to track people who come into clinics.

0:03:24.000,0:03:26.000
We have paper forms to track drug supplies,

0:03:26.000,0:03:29.000
blood supplies, all these different paper forms

0:03:29.000,0:03:31.000
for many different topics,

0:03:31.000,0:03:33.000
they all have a single common endpoint,

0:03:33.000,0:03:36.000
and the common endpoint looks something like this.

0:03:36.000,0:03:40.000
And what we're looking at here is a truckful o' data.

0:03:40.000,0:03:45.000
This is the data from a single vaccination coverage survey

0:03:45.000,0:03:47.000
in a single district in the country of Zambia

0:03:47.000,0:03:49.000
from a few years ago that I participated in.

0:03:49.000,0:03:52.000
The only thing anyone was trying to find out

0:03:52.000,0:03:55.000
is what percentage of Zambian children are vaccinated,

0:03:55.000,0:03:58.000
and this is the data, collected on paper over weeks

0:03:58.000,0:04:01.000
from a single district, which is something like a county

0:04:01.000,0:04:02.000
in the United States.

0:04:02.000,0:04:04.000
You can imagine that, for the entire country of Zambia,

0:04:04.000,0:04:08.000
answering just that single question

0:04:08.000,0:04:10.000
looks something like this.

0:04:10.000,0:04:12.000
Truck after truck after truck

0:04:12.000,0:04:16.000
filled with stack after stack after stack of data.

0:04:16.000,0:04:17.000
And what makes it even worse is that

0:04:17.000,0:04:19.000
that's just the beginning,

0:04:19.000,0:04:21.000
because once you've collected all that data,

0:04:21.000,0:04:23.000
of course someone's going to have to --

0:04:23.000,0:04:26.000
some unfortunate person is going to have to type that into a computer.

0:04:26.000,0:04:28.000
When I was a graduate student, I actually was

0:04:28.000,0:04:30.000
that unfortunate person sometimes.

0:04:30.000,0:04:33.000
I can tell you, I often wasn't really paying attention.

0:04:33.000,0:04:35.000
I probably made a lot of mistakes when I did it

0:04:35.000,0:04:38.000
that no one ever discovered, so data quality goes down.

0:04:38.000,0:04:41.000
But eventually that data hopefully gets typed into a computer,

0:04:41.000,0:04:43.000
and someone can begin to analyze it,

0:04:43.000,0:04:45.000
and once they have an analysis and a report,

0:04:45.000,0:04:49.000
hopefully then you can take the results of that data collection

0:04:49.000,0:04:51.000
and use it to vaccinate children better.

0:04:51.000,0:04:54.000
Because if there's anything worse

0:04:54.000,0:04:56.000
in the field of global public health,

0:04:56.000,0:04:59.000
I don't know what's worse than allowing children on this planet

0:04:59.000,0:05:02.000
to die of vaccine-preventable diseases,

0:05:02.000,0:05:05.000
diseases for which the vaccine costs a dollar.

0:05:05.000,0:05:08.000
And millions of children die of these diseases every year.

0:05:08.000,0:05:12.000
And the fact is, millions is a gross estimate because

0:05:12.000,0:05:15.000
we don't really know how many kids die each year of this.

0:05:15.000,0:05:17.000
What makes it even more frustrating is that

0:05:17.000,0:05:20.000
the data entry part, the part that I used to do as a grad student,

0:05:20.000,0:05:22.000
can take sometimes six months.

0:05:22.000,0:05:25.000
Sometimes it can take two years to type that information

0:05:25.000,0:05:28.000
into a computer, and sometimes, actually not infrequently,

0:05:28.000,0:05:30.000
it actually never happens.

0:05:30.000,0:05:32.000
Now try and wrap your head around that for a second.

0:05:32.000,0:05:35.000
You just had teams of hundreds of people.

0:05:35.000,0:05:37.000
They went out into the field to answer a particular question.

0:05:37.000,0:05:39.000
You probably spent hundreds of thousands of dollars

0:05:39.000,0:05:43.000
on fuel and photocopying and per diem,

0:05:43.000,0:05:46.000
and then for some reason, momentum is lost

0:05:46.000,0:05:47.000
or there's no money left,

0:05:47.000,0:05:49.000
and all of that comes to nothing

0:05:49.000,0:05:52.000
because no one actually types it into the computer at all.

0:05:52.000,0:05:55.000
The process just stops. Happens all the time.

0:05:55.000,0:05:58.000
This is what we base our decisions on in global health:

0:05:58.000,0:06:03.000
little data, old data, no data.

0:06:03.000,0:06:06.000
So back in 1995, I began to think about ways

0:06:06.000,0:06:08.000
in which we could improve this process.

0:06:08.000,0:06:11.000
Now 1995, obviously that was quite a long time ago.

0:06:11.000,0:06:13.000
It kind of frightens me to think of how long ago that was.

0:06:13.000,0:06:15.000
The top movie of the year was

0:06:15.000,0:06:16.000
"Die Hard with a Vengeance."

0:06:16.000,0:06:19.000
As you can see, Bruce Willis had a lot more hair back then.

0:06:19.000,0:06:22.000
I was working in the Centers for Disease Control,

0:06:22.000,0:06:25.000
and I had a lot more hair back then as well.

0:06:25.000,0:06:28.000
But to me, the most significant thing that I saw in 1995

0:06:28.000,0:06:29.000
was this.

0:06:29.000,0:06:32.000
Hard for us to imagine, but in 1995,

0:06:32.000,0:06:36.000
this was the ultimate elite mobile device.

0:06:36.000,0:06:38.000
Right? It wasn't an iPhone. It wasn't a Galaxy phone.

0:06:38.000,0:06:40.000
It was a Palm Pilot.

0:06:40.000,0:06:43.000
And when I saw the Palm Pilot for the first time, I thought,

0:06:43.000,0:06:46.000
why can't we put the forms on these Palm Pilots

0:06:46.000,0:06:48.000
and go out into the field just carrying one Palm Pilot,

0:06:48.000,0:06:52.000
which can hold the capacity of tens of thousands

0:06:52.000,0:06:54.000
of paper forms? Why don't we try to do that?

0:06:54.000,0:06:57.000
Because if we can do that, if we can actually just

0:06:57.000,0:06:59.000
collect the data electronically, digitally,

0:06:59.000,0:07:01.000
from the very beginning,

0:07:01.000,0:07:04.000
we can just put a shortcut right through that whole process

0:07:04.000,0:07:07.000
of typing,

0:07:07.000,0:07:09.000
of having somebody type that stuff into the computer.

0:07:09.000,0:07:11.000
We can skip straight to the analysis

0:07:11.000,0:07:14.000
and then straight to the use of the data to actually save lives.

0:07:14.000,0:07:17.000
So that's actually what I began to do.

0:07:17.000,0:07:20.000
Working at CDC, I began to travel to different programs

0:07:20.000,0:07:24.000
around the world and to train them in using Palm Pilots

0:07:24.000,0:07:27.000
to do data collection instead of using paper.

0:07:27.000,0:07:29.000
And it actually worked great.

0:07:29.000,0:07:31.000
It worked exactly as well as anybody would have predicted.

0:07:31.000,0:07:34.000
What do you know? Digital data collection

0:07:34.000,0:07:36.000
is actually more efficient than collecting on paper.

0:07:36.000,0:07:38.000
While I was doing it, my business partner, Rose,

0:07:38.000,0:07:41.000
who's here with her husband, Matthew, here in the audience,

0:07:41.000,0:07:44.000
Rose was out doing similar stuff for the American Red Cross.

0:07:44.000,0:07:46.000
The problem was, after a few years of doing that,

0:07:46.000,0:07:49.000
I realized I had done -- I had been to maybe

0:07:49.000,0:07:52.000
six or seven programs, and I thought,

0:07:52.000,0:07:54.000
you know, if I keep this up at this pace,

0:07:54.000,0:07:56.000
over my whole career, maybe I'm going to go

0:07:56.000,0:07:58.000
to maybe 20 or 30 programs.

0:07:58.000,0:08:01.000
But the problem is, 20 or 30 programs,

0:08:01.000,0:08:04.000
like, training 20 or 30 programs to use this technology,

0:08:04.000,0:08:06.000
that is a tiny drop in the bucket.

0:08:06.000,0:08:10.000
The demand for this, the need for data to run better programs,

0:08:10.000,0:08:13.000
just within health, not to mention all of the other fields

0:08:13.000,0:08:15.000
in developing countries, is enormous.

0:08:15.000,0:08:19.000
There are millions and millions and millions of programs,

0:08:19.000,0:08:22.000
millions of clinics that need to track drugs,

0:08:22.000,0:08:23.000
millions of vaccine programs.

0:08:23.000,0:08:25.000
There are schools that need to track attendance.

0:08:25.000,0:08:27.000
There are all these different things

0:08:27.000,0:08:29.000
for us to get the data that we need to do.

0:08:29.000,0:08:34.000
And I realized, if I kept up the way that I was doing,

0:08:34.000,0:08:37.000
I was basically hardly going to make any impact

0:08:37.000,0:08:39.000
by the end of my career.

0:08:39.000,0:08:41.000
And so I began to wrack my brain

0:08:41.000,0:08:42.000
trying to think about, you know,

0:08:42.000,0:08:44.000
what was the process that I was doing,

0:08:44.000,0:08:47.000
how was I training folks, and what were the bottlenecks

0:08:47.000,0:08:49.000
and what were the obstacles to doing it faster

0:08:49.000,0:08:51.000
and to doing it more efficiently?

0:08:51.000,0:08:54.000
And unfortunately, after thinking about this for some time,

0:08:54.000,0:08:58.000
I realized -- I identified the main obstacle.

0:08:58.000,0:09:00.000
And the main obstacle, it turned out,

0:09:00.000,0:09:01.000
and this is a sad realization,

0:09:01.000,0:09:04.000
the main obstacle was me.

0:09:04.000,0:09:06.000
So what do I mean by that?

0:09:06.000,0:09:08.000
I had developed a process whereby

0:09:08.000,0:09:13.000
I was the center of the universe of this technology.

0:09:13.000,0:09:16.000
If you wanted to use this technology, you had to get in touch with me.

0:09:16.000,0:09:18.000
That means you had to know I existed.

0:09:18.000,0:09:20.000
Then you had to find the money to pay for me

0:09:20.000,0:09:21.000
to fly out to your country

0:09:21.000,0:09:23.000
and the money to pay for my hotel

0:09:23.000,0:09:26.000
and my per diem and my daily rate.

0:09:26.000,0:09:29.000
So you could be talking about 10,000 or 20,000 or 30,000 dollars

0:09:29.000,0:09:31.000
if I actually had the time or it fit my schedule

0:09:31.000,0:09:33.000
and I wasn't on vacation.

0:09:33.000,0:09:36.000
The point is that anything, any system that depends

0:09:36.000,0:09:39.000
on a single human being or two or three or five human beings,

0:09:39.000,0:09:41.000
it just doesn't scale.

0:09:41.000,0:09:43.000
And this is a problem for which we need to scale

0:09:43.000,0:09:46.000
this technology and we need to scale it now.

0:09:46.000,0:09:48.000
And so I began to think of ways in which I could basically

0:09:48.000,0:09:50.000
take myself out of the picture.

0:09:50.000,0:09:55.000
And, you know, I was thinking,

0:09:55.000,0:09:57.000
how could I take myself out of the picture

0:09:57.000,0:09:59.000
for quite some time.

0:09:59.000,0:10:01.000
You know, I'd been trained that the way that

0:10:01.000,0:10:04.000
you distribute technology within international development

0:10:04.000,0:10:06.000
is always consultant-based.

0:10:06.000,0:10:09.000
It's always guys that look pretty much like me

0:10:09.000,0:10:11.000
flying from countries that look pretty much like this

0:10:11.000,0:10:14.000
to other countries with people with darker skin.

0:10:14.000,0:10:17.000
And you go out there, and you spend money on airfare

0:10:17.000,0:10:20.000
and you spend time and you spend per diem

0:10:20.000,0:10:22.000
and you spend [on a] hotel and you spend all that stuff.

0:10:22.000,0:10:24.000
As far as I knew, that was the only way

0:10:24.000,0:10:27.000
you could distribute technology, and I couldn't figure out a way around it.

0:10:27.000,0:10:30.000
But the miracle that happened,

0:10:30.000,0:10:33.000
I'm going to call it Hotmail for short.

0:10:33.000,0:10:35.000
Now you may not think of Hotmail as being miraculous,

0:10:35.000,0:10:38.000
but for me it was miraculous, because I noticed,

0:10:38.000,0:10:40.000
just as I was wrestling with this problem,

0:10:40.000,0:10:44.000
I was working in sub-Saharan Africa mostly at the time.

0:10:44.000,0:10:46.000
I noticed that every sub-Saharan African health worker

0:10:46.000,0:10:50.000
that I was working with had a Hotmail account.

0:10:50.000,0:10:53.000
And I thought, it struck me,

0:10:53.000,0:10:55.000
wait a minute, I know that the Hotmail people

0:10:55.000,0:10:58.000
surely didn't fly to the Ministry of Health of Kenya

0:10:58.000,0:11:01.000
to train people in how to use Hotmail.

0:11:01.000,0:11:03.000
So these guys are distributing technology.

0:11:03.000,0:11:05.000
They're getting software capacity out there

0:11:05.000,0:11:07.000
but they're not actually flying around the world.

0:11:07.000,0:11:09.000
I need to think about this some more.

0:11:09.000,0:11:11.000
While I was thinking about it, people started using

0:11:11.000,0:11:14.000
even more things just like this, just as we were.

0:11:14.000,0:11:15.000
They started using LinkedIn and Flickr

0:11:15.000,0:11:18.000
and Gmail and Google Maps, all these things.

0:11:18.000,0:11:21.000
Of course, all of these things are cloud-based

0:11:21.000,0:11:23.000
and don't require any training.

0:11:23.000,0:11:25.000
They don't require any programmers.

0:11:25.000,0:11:26.000
They don't require any consultants, because

0:11:26.000,0:11:29.000
the business model for all these businesses

0:11:29.000,0:11:32.000
requires that something be so simple we can use it ourselves

0:11:32.000,0:11:33.000
with little or no training.

0:11:33.000,0:11:35.000
You just have to hear about it and go to the website.

0:11:35.000,0:11:40.000
And so I thought, what would happen if we built software

0:11:40.000,0:11:42.000
to do what I'd been consulting in?

0:11:42.000,0:11:43.000
Instead of training people how

0:11:43.000,0:11:46.000
to put forms onto mobile devices,

0:11:46.000,0:11:48.000
let's create software that lets them do it themselves

0:11:48.000,0:11:50.000
with no training and without me being involved?

0:11:50.000,0:11:52.000
And that's exactly what we did.

0:11:52.000,0:11:56.000
So we created software called Magpi,

0:11:56.000,0:11:58.000
which has an online form creator.

0:11:58.000,0:11:59.000
No one has to speak to me.

0:11:59.000,0:12:02.000
You just have to hear about it and go to the website.

0:12:02.000,0:12:04.000
You can create forms, and once you've created the forms,

0:12:04.000,0:12:07.000
you push them to a variety of common mobile phones.

0:12:07.000,0:12:09.000
Obviously nowadays, we've moved past Palm Pilots

0:12:09.000,0:12:10.000
to mobile phones.

0:12:10.000,0:12:12.000
And it doesn't have to be a smartphone.

0:12:12.000,0:12:14.000
It can be a basic phone like the phone on the right there,

0:12:14.000,0:12:16.000
you know, the basic kind of Symbian phone

0:12:16.000,0:12:18.000
that's very common in developing countries.

0:12:18.000,0:12:22.000
And the great part about this is, it's just like Hotmail.

0:12:22.000,0:12:24.000
It's cloud-based, and it doesn't require any training,

0:12:24.000,0:12:26.000
programming, consultants.

0:12:26.000,0:12:28.000
But there are some additional benefits as well.

0:12:28.000,0:12:30.000
Now we knew, when we built this system,

0:12:30.000,0:12:33.000
the whole point of it, just like with the Palm Pilots,

0:12:33.000,0:12:35.000
was that you'd have to, you'd be able to

0:12:35.000,0:12:38.000
collect the data and immediately upload the data and get your data set.

0:12:38.000,0:12:41.000
But what we found, of course, since it's already on a computer,

0:12:41.000,0:12:44.000
we can deliver instant maps and analysis and graphing.

0:12:44.000,0:12:46.000
We can take a process that took two years

0:12:46.000,0:12:49.000
and compress that down to the space of five minutes.

0:12:49.000,0:12:52.000
Unbelievable improvements in efficiency.

0:12:52.000,0:12:57.000
Cloud-based, no training, no consultants, no me.

0:12:57.000,0:12:59.000
And I told you that in the first few years

0:12:59.000,0:13:01.000
of trying to do this the old-fashioned way,

0:13:01.000,0:13:02.000
going out to each country,

0:13:02.000,0:13:05.000
we reached about, I don't know,

0:13:05.000,0:13:07.000
probably trained about 1,000 people.

0:13:07.000,0:13:09.000
What happened after we did this?

0:13:09.000,0:13:12.000
In the second three years, we had 14,000 people

0:13:12.000,0:13:15.000
find the website, sign up, and start using it to collect data,

0:13:15.000,0:13:16.000
data for disaster response,

0:13:16.000,0:13:21.000
Canadian pig farmers tracking pig disease and pig herds,

0:13:21.000,0:13:24.000
people tracking drug supplies.

0:13:24.000,0:13:25.000
One of my favorite examples, the IRC,

0:13:25.000,0:13:27.000
International Rescue Committee,

0:13:27.000,0:13:30.000
they have a program where semi-literate midwives

0:13:30.000,0:13:33.000
using $10 mobile phones

0:13:33.000,0:13:35.000
send a text message using our software

0:13:35.000,0:13:37.000
once a week with the number of births

0:13:37.000,0:13:40.000
and the number of deaths, which gives IRC

0:13:40.000,0:13:42.000
something that no one in global health has ever had:

0:13:42.000,0:13:46.000
a near real-time system of counting babies,

0:13:46.000,0:13:47.000
of knowing how many kids are born,

0:13:47.000,0:13:49.000
of knowing how many children there are

0:13:49.000,0:13:52.000
in Sierra Leone, which is the country where this is happening,

0:13:52.000,0:13:55.000
and knowing how many children die.

0:13:55.000,0:13:56.000
Physicians for Human Rights --

0:13:56.000,0:13:59.000
this is moving a little bit outside the health field —

0:13:59.000,0:14:02.000
they are gathering, they're basically training people

0:14:02.000,0:14:05.000
to do rape exams in Congo, where this is an epidemic,

0:14:05.000,0:14:07.000
a horrible epidemic,

0:14:07.000,0:14:09.000
and they're using our software to document

0:14:09.000,0:14:12.000
the evidence they find, including photographically,

0:14:12.000,0:14:16.000
so that they can bring the perpetrators to justice.

0:14:16.000,0:14:20.000
Camfed, another charity based out of the U.K.,

0:14:20.000,0:14:24.000
Camfed pays girls' families to keep them in school.

0:14:24.000,0:14:26.000
They understand this is the most significant intervention

0:14:26.000,0:14:29.000
they can make. They used to track the dispersements,

0:14:29.000,0:14:31.000
the attendance, the grades, on paper.

0:14:31.000,0:14:32.000
The turnaround time between a teacher

0:14:32.000,0:14:34.000
writing down grades or attendance

0:14:34.000,0:14:37.000
and getting that into a report was about two to three years.

0:14:37.000,0:14:39.000
Now it's real time, and because this is such

0:14:39.000,0:14:42.000
a low-cost system and based in the cloud, it costs,

0:14:42.000,0:14:45.000
for the entire five countries that Camfed runs this in

0:14:45.000,0:14:47.000
with tens of thousands of girls,

0:14:47.000,0:14:51.000
the whole cost combined is 10,000 dollars a year.

0:14:51.000,0:14:52.000
That's less than I used to get

0:14:52.000,0:14:58.000
just traveling out for two weeks to do a consultation.

0:14:58.000,0:15:00.000
So I told you before that

0:15:00.000,0:15:02.000
when we were doing it the old-fashioned way, I realized

0:15:02.000,0:15:05.000
all of our work was really adding up to just a drop in the bucket --

0:15:05.000,0:15:07.000
10, 20, 30 different programs.

0:15:07.000,0:15:09.000
We've made a lot of progress, but I recognize

0:15:09.000,0:15:11.000
that right now, even the work that we've done

0:15:11.000,0:15:14.000
with 14,000 people using this,

0:15:14.000,0:15:17.000
is still a drop in the bucket. But something's changed.

0:15:17.000,0:15:18.000
And I think it should be obvious.

0:15:18.000,0:15:20.000
What's changed now is,

0:15:20.000,0:15:24.000
instead of having a program in which we're scaling at such a slow rate

0:15:24.000,0:15:27.000
that we can never reach all the people who need us,

0:15:27.000,0:15:31.000
we've made it unnecessary for people to get reached by us.

0:15:31.000,0:15:34.000
We've created a tool that lets programs

0:15:34.000,0:15:37.000
keep kids in school, track the number of babies

0:15:37.000,0:15:40.000
that are born and the number of babies that die,

0:15:40.000,0:15:43.000
to catch criminals and successfully prosecute them,

0:15:43.000,0:15:46.000
to do all these different things to learn more

0:15:46.000,0:15:51.000
about what's going on, to understand more, to see more,

0:15:51.000,0:15:55.000
and to save lives and improve lives.

0:15:55.000,0:15:57.000
Thank you.

0:15:57.000,0:16:01.000
(Applause)