full transcript
"From the Ted Talk by Mallory Freeman: Your company's data could help end world hunger"

Unscramble the Blue Letters

Now, companies will say, "Ah! Don't take our decision scientists from us. We need every spare second of their time." But there's a way. If a company was going to dntaoe a block of a decision scientist's time, it would actually make more sense to spread out that block of time over a long prioed, say for example five years. This might only amount to a couple of hours per month, which a company would hardly miss, but what it enebals is really important: long-term partnerships. Long-term partnerships allow you to build relationships, to get to know the data, to really understand it and to start to understand the needs and celahengls that the humanitarian organization is facing. In Rome, at the World Food pamrgmroe, this took us five years to do, five years. That first three years, OK, that was just what we couldn't solve for. Then there was two yraes after that of refining and implementing the tool, like in the operations in Iraq and other countries. I don't think that's an unrealistic timeline when it comes to using data to make operational changes. It's an investment. It requires ptiaence. But the tyeps of results that can be pucrdeod are undeniable. In our case, it was the aitilby to feed tens of thousands more people.

Open Cloze

Now, companies will say, "Ah! Don't take our decision scientists from us. We need every spare second of their time." But there's a way. If a company was going to ______ a block of a decision scientist's time, it would actually make more sense to spread out that block of time over a long ______, say for example five years. This might only amount to a couple of hours per month, which a company would hardly miss, but what it _______ is really important: long-term partnerships. Long-term partnerships allow you to build relationships, to get to know the data, to really understand it and to start to understand the needs and __________ that the humanitarian organization is facing. In Rome, at the World Food _________, this took us five years to do, five years. That first three years, OK, that was just what we couldn't solve for. Then there was two _____ after that of refining and implementing the tool, like in the operations in Iraq and other countries. I don't think that's an unrealistic timeline when it comes to using data to make operational changes. It's an investment. It requires ________. But the _____ of results that can be ________ are undeniable. In our case, it was the _______ to feed tens of thousands more people.

Solution

  1. produced
  2. enables
  3. ability
  4. period
  5. years
  6. challenges
  7. patience
  8. donate
  9. types
  10. programme

Original Text

Now, companies will say, "Ah! Don't take our decision scientists from us. We need every spare second of their time." But there's a way. If a company was going to donate a block of a decision scientist's time, it would actually make more sense to spread out that block of time over a long period, say for example five years. This might only amount to a couple of hours per month, which a company would hardly miss, but what it enables is really important: long-term partnerships. Long-term partnerships allow you to build relationships, to get to know the data, to really understand it and to start to understand the needs and challenges that the humanitarian organization is facing. In Rome, at the World Food Programme, this took us five years to do, five years. That first three years, OK, that was just what we couldn't solve for. Then there was two years after that of refining and implementing the tool, like in the operations in Iraq and other countries. I don't think that's an unrealistic timeline when it comes to using data to make operational changes. It's an investment. It requires patience. But the types of results that can be produced are undeniable. In our case, it was the ability to feed tens of thousands more people.

ngrams of length 2

collocation frequency
decision scientists 9
data philanthropy 5
million options 3
humanitarian world 3
donating technology 3
donating decision 3
donating data 3

ngrams of length 3

collocation frequency
donating decision scientists 3

Important Words

  1. ability
  2. amount
  3. block
  4. build
  5. case
  6. challenges
  7. companies
  8. company
  9. countries
  10. couple
  11. data
  12. decision
  13. donate
  14. enables
  15. facing
  16. feed
  17. food
  18. hours
  19. humanitarian
  20. implementing
  21. investment
  22. iraq
  23. long
  24. month
  25. operational
  26. operations
  27. organization
  28. partnerships
  29. patience
  30. people
  31. period
  32. produced
  33. programme
  34. refining
  35. relationships
  36. requires
  37. results
  38. rome
  39. scientists
  40. sense
  41. solve
  42. spare
  43. spread
  44. start
  45. tens
  46. thousands
  47. time
  48. timeline
  49. tool
  50. types
  51. undeniable
  52. understand
  53. unrealistic
  54. world
  55. years