TED@UPS
Mallory Freeman: Your company's data could help end world hunger
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Your company might have donated money to help solve humanitarian issues, but you could have something even more useful to offer: your data. Mallory Freeman shows us how private sector companies can help make real progress on big problems -- from the refugee crisis to world hunger -- by donating untapped data and decision scientists. What might your company be able to contribute?
Mallory Freeman - Data activist
UPS's advanced analytics manager Mallory Freeman researches how to do the most good with data. Full bio
UPS's advanced analytics manager Mallory Freeman researches how to do the most good with data. Full bio
Double-click the English transcript below to play the video.
00:12
June 2010.
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I landed for the first time
in Rome, Italy.
in Rome, Italy.
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I wasn't there to sightsee.
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I was there to solve world hunger.
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(Laughter)
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That's right.
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I was a 25-year-old PhD student
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armed with a prototype tool
developed back at my university,
developed back at my university,
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and I was going to help
the World Food Programme fix hunger.
the World Food Programme fix hunger.
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So I strode into the headquarters building
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and my eyes scanned the row of UN flags,
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and I smiled as I thought to myself,
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"The engineer is here."
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(Laughter)
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Give me your data.
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I'm going to optimize everything.
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(Laughter)
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Tell me the food that you've purchased,
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tell me where it's going
and when it needs to be there,
and when it needs to be there,
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and I'm going to tell you
the shortest, fastest, cheapest,
the shortest, fastest, cheapest,
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best set of routes to take for the food.
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We're going to save money,
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we're going to avoid
delays and disruptions,
delays and disruptions,
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and bottom line,
we're going to save lives.
we're going to save lives.
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You're welcome.
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(Laughter)
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I thought it was going to take 12 months,
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OK, maybe even 13.
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This is not quite how it panned out.
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Just a couple of months into the project,
my French boss, he told me,
my French boss, he told me,
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"You know, Mallory,
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it's a good idea,
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but the data you need
for your algorithms is not there.
for your algorithms is not there.
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It's the right idea but at the wrong time,
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and the right idea at the wrong time
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is the wrong idea."
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(Laughter)
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Project over.
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I was crushed.
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When I look back now
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on that first summer in Rome
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and I see how much has changed
over the past six years,
over the past six years,
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it is an absolute transformation.
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It's a coming of age for bringing data
into the humanitarian world.
into the humanitarian world.
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It's exciting. It's inspiring.
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But we're not there yet.
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And brace yourself, executives,
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because I'm going to be putting companies
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on the hot seat to step up
and play the role that I know they can.
and play the role that I know they can.
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My experiences back in Rome prove
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using data you can save lives.
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OK, not that first attempt,
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but eventually we got there.
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Let me paint the picture for you.
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Imagine that you have to plan
breakfast, lunch and dinner
breakfast, lunch and dinner
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for 500,000 people,
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and you only have
a certain budget to do it,
a certain budget to do it,
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say 6.5 million dollars per month.
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Well, what should you do?
What's the best way to handle it?
What's the best way to handle it?
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Should you buy rice, wheat, chickpea, oil?
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How much?
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It sounds simple. It's not.
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You have 30 possible foods,
and you have to pick five of them.
and you have to pick five of them.
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That's already over 140,000
different combinations.
different combinations.
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Then for each food that you pick,
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you need to decide how much you'll buy,
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where you're going to get it from,
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where you're going to store it,
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how long it's going to take to get there.
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You need to look at all of the different
transportation routes as well.
transportation routes as well.
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And that's already
over 900 million options.
over 900 million options.
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If you considered each option
for a single second,
for a single second,
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that would take you
over 28 years to get through.
over 28 years to get through.
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900 million options.
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So we created a tool
that allowed decisionmakers
that allowed decisionmakers
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to weed through all 900 million options
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in just a matter of days.
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It turned out to be incredibly successful.
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In an operation in Iraq,
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we saved 17 percent of the costs,
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and this meant that you had the ability
to feed an additional 80,000 people.
to feed an additional 80,000 people.
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It's all thanks to the use of data
and modeling complex systems.
and modeling complex systems.
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But we didn't do it alone.
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The unit that I worked with in Rome,
they were unique.
they were unique.
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They believed in collaboration.
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They brought in the academic world.
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They brought in companies.
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And if we really want to make big changes
in big problems like world hunger,
in big problems like world hunger,
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we need everybody to the table.
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We need the data people
from humanitarian organizations
from humanitarian organizations
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leading the way,
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and orchestrating
just the right types of engagements
just the right types of engagements
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with academics, with governments.
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And there's one group that's not being
leveraged in the way that it should be.
leveraged in the way that it should be.
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Did you guess it? Companies.
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Companies have a major role to play
in fixing the big problems in our world.
in fixing the big problems in our world.
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I've been in the private sector
for two years now.
for two years now.
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I've seen what companies can do,
and I've seen what companies aren't doing,
and I've seen what companies aren't doing,
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and I think there's three main ways
that we can fill that gap:
that we can fill that gap:
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by donating data,
by donating decision scientists
by donating decision scientists
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and by donating technology
to gather new sources of data.
to gather new sources of data.
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This is data philanthropy,
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and it's the future of corporate
social responsibility.
social responsibility.
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Bonus, it also makes good business sense.
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Companies today,
they collect mountains of data,
they collect mountains of data,
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so the first thing they can do
is start donating that data.
is start donating that data.
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Some companies are already doing it.
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Take, for example,
a major telecom company.
a major telecom company.
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They opened up their data
in Senegal and the Ivory Coast
in Senegal and the Ivory Coast
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and researchers discovered
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that if you look at the patterns
in the pings to the cell phone towers,
in the pings to the cell phone towers,
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you can see where people are traveling.
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And that can tell you things like
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where malaria might spread,
and you can make predictions with it.
and you can make predictions with it.
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Or take for example
an innovative satellite company.
an innovative satellite company.
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They opened up their data and donated it,
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and with that data you could track
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how droughts are impacting
food production.
food production.
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With that you can actually trigger
aid funding before a crisis can happen.
aid funding before a crisis can happen.
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This is a great start.
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There's important insights
just locked away in company data.
just locked away in company data.
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And yes, you need to be very careful.
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You need to respect privacy concerns,
for example by anonymizing the data.
for example by anonymizing the data.
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But even if the floodgates opened up,
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and even if all companies
donated their data
donated their data
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to academics, to NGOs,
to humanitarian organizations,
to humanitarian organizations,
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it wouldn't be enough
to harness that full impact of data
to harness that full impact of data
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for humanitarian goals.
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Why?
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To unlock insights in data,
you need decision scientists.
you need decision scientists.
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Decision scientists are people like me.
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They take the data, they clean it up,
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transform it and put it
into a useful algorithm
into a useful algorithm
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that's the best choice
to address the business need at hand.
to address the business need at hand.
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In the world of humanitarian aid,
there are very few decision scientists.
there are very few decision scientists.
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Most of them work for companies.
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So that's the second thing
that companies need to do.
that companies need to do.
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In addition to donating their data,
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they need to donate
their decision scientists.
their decision scientists.
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Now, companies will say, "Ah! Don't take
our decision scientists from us.
our decision scientists from us.
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We need every spare second of their time."
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But there's a way.
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If a company was going to donate
a block of a decision scientist's time,
a block of a decision scientist's time,
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it would actually make more sense
to spread out that block of time
to spread out that block of time
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over a long period,
say for example five years.
say for example five years.
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This might only amount
to a couple of hours per month,
to a couple of hours per month,
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which a company would hardly miss,
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but what it enables is really important:
long-term partnerships.
long-term partnerships.
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Long-term partnerships
allow you to build relationships,
allow you to build relationships,
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to get to know the data,
to really understand it
to really understand it
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and to start to understand
the needs and challenges
the needs and challenges
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that the humanitarian
organization is facing.
organization is facing.
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In Rome, at the World Food Programme,
this took us five years to do,
this took us five years to do,
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five years.
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That first three years, OK,
that was just what we couldn't solve for.
that was just what we couldn't solve for.
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Then there was two years after that
of refining and implementing the tool,
of refining and implementing the tool,
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like in the operations in Iraq
and other countries.
and other countries.
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I don't think that's
an unrealistic timeline
an unrealistic timeline
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when it comes to using data
to make operational changes.
to make operational changes.
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It's an investment. It requires patience.
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But the types of results
that can be produced are undeniable.
that can be produced are undeniable.
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In our case, it was the ability
to feed tens of thousands more people.
to feed tens of thousands more people.
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So we have donating data,
we have donating decision scientists,
we have donating decision scientists,
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and there's actually a third way
that companies can help:
that companies can help:
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donating technology
to capture new sources of data.
to capture new sources of data.
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You see, there's a lot of things
we just don't have data on.
we just don't have data on.
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Right now, Syrian refugees
are flooding into Greece,
are flooding into Greece,
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and the UN refugee agency,
they have their hands full.
they have their hands full.
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The current system for tracking people
is paper and pencil,
is paper and pencil,
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and what that means is
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that when a mother and her five children
walk into the camp,
walk into the camp,
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headquarters is essentially
blind to this moment.
blind to this moment.
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That's all going to change
in the next few weeks,
in the next few weeks,
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thanks to private sector collaboration.
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There's going to be a new system based
on donated package tracking technology
on donated package tracking technology
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from the logistics company
that I work for.
that I work for.
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With this new system,
there will be a data trail,
there will be a data trail,
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so you know exactly the moment
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when that mother and her children
walk into the camp.
walk into the camp.
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And even more, you know
if she's going to have supplies
if she's going to have supplies
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this month and the next.
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Information visibility drives efficiency.
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For companies, using technology
to gather important data,
to gather important data,
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it's like bread and butter.
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They've been doing it for years,
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and it's led to major
operational efficiency improvements.
operational efficiency improvements.
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Just try to imagine
your favorite beverage company
your favorite beverage company
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trying to plan their inventory
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and not knowing how many bottles
were on the shelves.
were on the shelves.
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It's absurd.
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Data drives better decisions.
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Now, if you're representing a company,
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and you're pragmatic
and not just idealistic,
and not just idealistic,
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you might be saying to yourself,
"OK, this is all great, Mallory,
"OK, this is all great, Mallory,
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but why should I want to be involved?"
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Well for one thing, beyond the good PR,
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humanitarian aid
is a 24-billion-dollar sector,
is a 24-billion-dollar sector,
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and there's over five billion people,
maybe your next customers,
maybe your next customers,
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that live in the developing world.
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Further, companies that are engaging
in data philanthropy,
in data philanthropy,
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they're finding new insights
locked away in their data.
locked away in their data.
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Take, for example, a credit card company
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that's opened up a center
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that functions as a hub for academics,
for NGOs and governments,
for NGOs and governments,
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all working together.
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They're looking at information
in credit card swipes
in credit card swipes
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and using that to find insights
about how households in India
about how households in India
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live, work, earn and spend.
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For the humanitarian world,
this provides information
this provides information
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about how you might
bring people out of poverty.
bring people out of poverty.
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But for companies, it's providing
insights about your customers
insights about your customers
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and potential customers in India.
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It's a win all around.
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Now, for me, what I find
exciting about data philanthropy --
exciting about data philanthropy --
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donating data, donating decision
scientists and donating technology --
scientists and donating technology --
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it's what it means
for young professionals like me
for young professionals like me
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who are choosing to work at companies.
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Studies show that
the next generation of the workforce
the next generation of the workforce
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care about having their work
make a bigger impact.
make a bigger impact.
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We want to make a difference,
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and so through data philanthropy,
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companies can actually help engage
and retain their decision scientists.
and retain their decision scientists.
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And that's a big deal for a profession
that's in high demand.
that's in high demand.
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Data philanthropy
makes good business sense,
makes good business sense,
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and it also can help
revolutionize the humanitarian world.
revolutionize the humanitarian world.
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If we coordinated
the planning and logistics
the planning and logistics
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across all of the major facets
of a humanitarian operation,
of a humanitarian operation,
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we could feed, clothe and shelter
hundreds of thousands more people,
hundreds of thousands more people,
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and companies need to step up
and play the role that I know they can
and play the role that I know they can
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in bringing about this revolution.
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You've probably heard of the saying
"food for thought."
"food for thought."
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Well, this is literally thought for food.
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It finally is the right idea
at the right time.
at the right time.
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(Laughter)
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Très magnifique.
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Thank you.
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(Applause)
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ABOUT THE SPEAKER
Mallory Freeman - Data activistUPS's advanced analytics manager Mallory Freeman researches how to do the most good with data.
Why you should listen
Dr. Mallory Freeman is the Lead Data Scientist in the UPS Advanced Technology Group, working on research and development projects for UPS’s smart logistics network. She serves on the advisory board of Neighborhood Nexus, supporting data-driven insights for the greater Atlanta region.
Freeman earned her Ph.D. in industrial engineering from the Georgia Institute of Technology in 2014. Her thesis explored how to measure and improve humanitarian operations in practical ways -- with a special focus on the use of algorithms. While she was in graduate school, she helped lead supply chain optimization projects for the UN World Food Programme.
Freeman earned her Master's in operations research from MIT and her Bachelor's in industrial and systems engineering from Virginia Tech. In her spare time, she enjoys cooking, travelling and volunteering her data skills.
Mallory Freeman | Speaker | TED.com