Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2jEruds. Bo Peng goes over how Datascope iterated on the major pieces of the Expert Finder application project to produce actionable insights and recommendations on methodologies not only for the user interfaces, but also for our “expert finding” algorithms and data sources. Filmed at qconsf.com. Bo Peng is a partner and a data scientist at Datascope, a leading data science consultancy in Chicago, where she combines human centered design with analytics to derive actionable business insights for clients like P&G, Motorola, Thomson, Reuters. She is an active member of the technology community, co-organizing data science meetups and organizing the Women in Machine Learning & Data Science.

1. Bo Peng • @bo_p
Iterative design for data science projects
for QCon San Francisco • Nov 7, 2016

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Watch the video with slide
synchronization on InfoQ.com!
https://www.infoq.com/presentations/
iterative-design-data-science

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Strategy
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Highlights
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Presented at QCon San Francisco
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4. http://heritagehealthprize.com
Goal: Create an algorithm
that predicts how many
days a patient will spend in
a hospital in the next year.
case study: heritage health prize
approach

5. 2
1,363
25,316
years
teams
entries
http://heritagehealthprize.com
case study: heritage health prize
approach

6. score
time (in months)
constant value
all zeros
goal
http://heritagehealthprize.com
case study: heritage health prize
approach

7. score
time (in months)
constant value
all zeros
goal
http://heritagehealthprize.com
case study: heritage health prize
approach

8. score
time (in months)
constant value
all zeros
goal
http://heritagehealthprize.com
case study: heritage health prize
approach

9. score
time (in months)
constant value
all zeros
goal
http://heritagehealthprize.com
case study: heritage health prize
approach

10. score
time (in months)
constant value
all zeros
goal
http://heritagehealthprize.com
case study: heritage health prize
approach

11. score
time (in months)
constant value
all zeros
goal
http://heritagehealthprize.com
case study: heritage health prize
approach

12. score
constant value
all zeros
goal
What can we learn from this?
Solving business problems can rarely be
reduced to minimizing a model’s RMSE.

13. score
constant value
all zeros
goal
Contests are fun.
Solving business problems can rarely be
reduced to minimizing a model’s RMSE.

14. score
constant value
all zeros
goal
Contests are fun.
Solving business problems can rarely be
reduced to minimizing a model’s RMSE.

15. agenda
- A common approach to data science
- The design approach:
- a simple model goes along way (eDiscovery)
- finding & recommending experts within P&G

16. How simple models + design go a long way
Data driven e-discovery for Daegis

17. data-driven e-discovery
daegis

18. aboutpatent
not
aboutpatent
data-driven e-discovery
daegis

19. aboutpatent
not
aboutpatent
turn over to plaintiff
don’t
turn over to plaintiff
adverse inference
data-driven e-discovery
daegis

20. aboutpatent
not
aboutpatent
turn over to plaintiff
don’t
turn over to plaintiff
adverse inference
give away trade secrets
data-driven e-discovery
daegis

21. aboutpatent
not
aboutpatent
turn over to plaintiff
don’t
turn over to plaintiff
adverse inference
give away trade secrets
data-driven e-discovery
daegis

22. turn over to plaintiff
don’t
turn over to plaintiff
data-driven e-discovery
daegis

23. data-driven e-discovery
daegis

24. create a “document map”
algorithm design
patents
marketing
finances
fantasy football
lunch
coffee
data-driven e-discovery
daegis

25. create a “document map”
fantasy football
algorithm design
patents
lunch
marketing
finances
coffee
review away shades of grey
reduce reviews by 90-99%
data-driven e-discovery
daegis

27. care about design.
simple, powerful interfaces relay analytics better.

29. iterative problem solving
generate ideas
build prototypeevaluate
rapid
iterations
plan, build, test, and iterate as quickly as possible

30. Procter & Gamble
Data driven expertise exploration

31. data-driven expertise exploration
procter & gamble

32. data-driven expertise exploration
procter & gamble

33. High level goals:
- reveal areas of expertise
- evaluate connectivity within experts

35. data-driven expertise exploration
procter & gamble

36. Lorem Ipsum: a narrative about blankets.
Author: Charlie Brown
Date: 31 Jan 2012
Lorem Ipsum is a dummy text used when typesetting or marking up documents. It has a long
history starting from the 1500s and is still used in digital millennium for typesetting electronic
documents, page designs, etc.
In itself, the original text of Lorem Ipsum might have been taken from an ancient Latin book
that was written about 50 BC. Nevertheless, Lorem Ipsum’s words have been changed so
they don’t read as a proper text.
Naturally, page designs that are made for text documents must contain some text rather than
placeholder dots or something else. However, should they contain proper English words and
sentences almost every reader will deliberately try to interpret it eventually, missing the
design itself.
However, a placeholder text must have a natural distribution of letters and punctuation or
otherwise the markup will look strange and unnatural. That’s what Lorem Ipsum helps to
achieve.
I would like to thank Peppermint Pattyfor her support on studying Lorem
Ipsum as well as the infinite wisdom of Linus van Peltand his willingness to use
his blanket in my experiments.
data-driven expertise exploration
procter & gamble

38. vs.

39. vs.

40. iterative problem solving
generate ideas
build prototypeevaluate
rapid
iterations
plan, build, test, and iterate as quickly as possible

43. High level goals:
- reveal areas of expertise
- evaluate connectivity within experts

44. High level goals:
- reveal areas of expertise
- evaluate connectivity within experts

46. let’s compare countries.

48. + 1

50. 10 5 5 20
8 25 2 5
12 3 30 10
1 20 25 50

51. 10 5 5 20
8 25 2 5
12 3 30 10
1 20 25 50

52. 10 5 5 20
8 25 2 5
12 3 30 10
1 20 25 50

53. 10 5 5 20
8 25 2 5
12 3 30 10
1 20 25 50

55. design influences data science.

56. care about design.

57. Iterative design for data science projects
Bo Peng • @bo_p
for QCon San Francisco • Thanks!

58. Watch the video with slide
synchronization on InfoQ.com!
https://www.infoq.com/presentations/
iterative-design-data-science