Your company's data could help end world hunger | Mallory Freeman

52,762 views ใƒป 2016-11-29

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June 2010.
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I landed for the first time 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,
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and I was going to help 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,
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and I'm going to tell you 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,
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and bottom line, 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,
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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.
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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,
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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.
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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.
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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
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for 500,000 people,
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and you only have 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?
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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.
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That's already over 140,000 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.
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And that's already over 900 million options.
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If you considered each option for a single second,
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that would take you 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
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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.
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It's all thanks to the use of data 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.
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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,
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we need everybody to the table.
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We need the data people from humanitarian organizations
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leading the way,
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and orchestrating 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.
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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.
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I've been in the private sector for two years now.
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I've seen what companies can do, 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:
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by donating data, by donating decision scientists
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and by donating technology 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.
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Bonus, it also makes good business sense.
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Companies today, they collect mountains of data,
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so the first thing they can do 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.
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They opened up their data 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,
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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.
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Or take for example 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.
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With that you can actually trigger 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.
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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.
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But even if the floodgates opened up,
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and even if all companies donated their data
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to academics, to NGOs, to humanitarian organizations,
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it wouldn't be enough 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.
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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
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that's the best choice to address the business need at hand.
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In the world of humanitarian aid, 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.
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In addition to donating their data,
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they need to donate their decision scientists.
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Now, companies will say, "Ah! Don't take 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,
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it would actually make more sense to spread out that block of time
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over a long period, say for example five years.
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This might only amount 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.
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Long-term partnerships allow you to build relationships,
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to get to know the data, to really understand it
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and to start to understand the needs and challenges
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that the humanitarian organization is facing.
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In Rome, at the World Food Programme, 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.
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Then there was two years after that of refining and implementing the tool,
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like in the operations in Iraq and other countries.
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I don't think that's an unrealistic timeline
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when it comes to using data 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.
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In our case, it was the ability to feed tens of thousands more people.
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So we have donating data, we have donating decision scientists,
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and there's actually a third way that companies can help:
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donating technology 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.
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Right now, Syrian refugees are flooding into Greece,
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and the UN refugee agency, they have their hands full.
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The current system for tracking people 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,
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headquarters is essentially blind to this moment.
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That's all going to change 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
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from the logistics company that I work for.
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With this new system, 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.
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And even more, you know 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,
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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.
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Just try to imagine 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.
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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,
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you might be saying to yourself, "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,
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and there's over five billion people, 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,
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they're finding new insights 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,
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all working together.
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They're looking at information in credit card swipes
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and using that to find insights 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
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about how you might bring people out of poverty.
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But for companies, it's providing 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 --
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donating data, donating decision scientists and donating technology --
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it's what it means 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
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care about having their work 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.
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And that's a big deal for a profession that's in high demand.
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Data philanthropy makes good business sense,
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and it also can help revolutionize the humanitarian world.
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If we coordinated the planning and logistics
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across all of the major facets of a humanitarian operation,
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we could feed, clothe and shelter hundreds of thousands more people,
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and companies need to step up 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."
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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.
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(Laughter)
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Trรจs magnifique.
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Thank you.
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(Applause)
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