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solve for ambiguity
what the data literate can learn from the design process

@deanmalmgren
@DsAtweet
2014 february
norc
data scientists thrive with ambiguity
solve for x

Ax=b

optimize
f(x)

optimize
“our profitability”

project evolution

x=...
origins of ambiguity
many feasible approaches

@deanmalmgren | bit.ly/design-data
origins of ambiguity
unclear problems

identify the best locations to plant new trees

@deanmalmgren | bit.ly/design-data
origins of ambiguity
unclear problems

identify the best locations to plant new trees
aesthetically pleasing?
maximize gro...
“design process” is used everywhere
anticipate failure
generate
hypotheses

evaluate
feedback

1-4 week
iterations

build
...
“design process” is used everywhere
anticipate failure
human-centered design
lean startup
agile programming

evaluate
feed...
design and data science
challenges in practice
problem lost in translation

generate
hypotheses

takes a long time to
coll...
a project always starts with…

@deanmalmgren | bit.ly/design-data
a project always starts with…

@deanmalmgren | bit.ly/design-data
a project always starts with…

@deanmalmgren | bit.ly/design-data
a project always starts with…

Kathie was promoted

@deanmalmgren | bit.ly/design-data
informal conversation to stated goals
mostly bad ideas, but a few good ones

@deanmalmgren | bit.ly/design-data
informal conversation to stated goals
mostly bad ideas, but a few good ones

Lorem Ipsum: a narrative about blankets.

Cha...
informal conversation to stated goals
mostly bad ideas, but a few good ones

Lorem Ipsum: a narrative about blankets.

Cha...
informal conversation to stated goals
mostly bad ideas, but a few good ones

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

@deanmalmgren | bit.ly/design-data
concept sketch comparisons
qualitative a/b testing

search engine
with relevance metrics

demographics

human readable
exp...
from sketch to blue print
add detail to get feedback (while building)

@deanmalmgren | bit.ly/design-data
from sketch to blue print
add detail to get feedback (while building)

@deanmalmgren | bit.ly/design-data
from sketch to blue print
add detail to get feedback (while building)

@deanmalmgren | bit.ly/design-data
prototype iterations
faux first; KISS; build for feedback

@deanmalmgren | bit.ly/design-data
prototype iterations
faux first; KISS; build for feedback

@deanmalmgren | bit.ly/design-data
prototype iterations
faux first; KISS; build for feedback

@deanmalmgren | bit.ly/design-data
prototype iterations
faux first; KISS; build for feedback

@deanmalmgren | bit.ly/design-data
tips for designing with data
problem lost in translation

generate
hypotheses

takes a long time to
collect data, analyze,...
solve ambiguous problems
with an iterative approach
http://bit.ly/design-data
!

@deanmalmgren
dean.malmgren@datascopeanal...
Solving for ambiguity: what the data literate can learn from the design process
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Solving for ambiguity: what the data literate can learn from the design process

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This was presented during Innovation Days at NORC on 2014.02.25

Regardless of whether you call it "business intelligence", "big data", "analytics" or just plain old "math", we have many tried and true techniques for dealing with uncertainty. But ambiguity is a separate matter and, at least in my experience, is the hardest part of creating value from data. During this talk, I will illustrate how the design process can be used to solve ambiguous problems by drawing on projects we've done at Datascope.

Published in: Design
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Solving for ambiguity: what the data literate can learn from the design process

  1. 1. solve for ambiguity what the data literate can learn from the design process @deanmalmgren @DsAtweet 2014 february norc
  2. 2. data scientists thrive with ambiguity solve for x Ax=b optimize f(x) optimize “our profitability” project evolution x=5+2 optimize Ax=b subject to f(x) > 0 @deanmalmgren | bit.ly/design-data
  3. 3. origins of ambiguity many feasible approaches @deanmalmgren | bit.ly/design-data
  4. 4. origins of ambiguity unclear problems identify the best locations to plant new trees @deanmalmgren | bit.ly/design-data
  5. 5. origins of ambiguity unclear problems identify the best locations to plant new trees aesthetically pleasing? maximize growth? increase foliage? offset CO2 emissions? how many? what kinds of trees? move old trees? replace old trees? @deanmalmgren | bit.ly/design-data
  6. 6. “design process” is used everywhere anticipate failure generate hypotheses evaluate feedback 1-4 week iterations build prototype @deanmalmgren | bit.ly/design-data
  7. 7. “design process” is used everywhere anticipate failure human-centered design lean startup agile programming evaluate feedback generate hypotheses personas, scenarios, use cases business/product requirements story/user cards 1-4 week iterations build prototype surveys, interviews, focus groups split testing, A/B testing QA; requirements churn build device prototypes minimum viable product write code @deanmalmgren | bit.ly/design-data
  8. 8. design and data science challenges in practice problem lost in translation generate hypotheses takes a long time to collect data, analyze, and build visualization evaluate feedback 1-4 week iterations build prototype proof is in the pudding @deanmalmgren | bit.ly/design-data
  9. 9. a project always starts with… @deanmalmgren | bit.ly/design-data
  10. 10. a project always starts with… @deanmalmgren | bit.ly/design-data
  11. 11. a project always starts with… @deanmalmgren | bit.ly/design-data
  12. 12. a project always starts with… Kathie was promoted @deanmalmgren | bit.ly/design-data
  13. 13. informal conversation to stated goals mostly bad ideas, but a few good ones @deanmalmgren | bit.ly/design-data
  14. 14. informal conversation to stated goals mostly bad ideas, but a few good ones Lorem Ipsum: a narrative about blankets. Charlie Brown Date: 31 Jan 2012 ! Author: 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. ! Peppermint Patty for her support on studying Lorem Ipsum as well as the infinite wisdom of Linus van Pelt and his I would like to thank willingness to use his blanket in my experiments. @deanmalmgren | bit.ly/design-data
  15. 15. informal conversation to stated goals mostly bad ideas, but a few good ones Lorem Ipsum: a narrative about blankets. Charlie Brown Date: 31 Jan 2012 ! Author: 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. ! Peppermint Patty for her support on studying Lorem Ipsum as well as the infinite wisdom of Linus van Pelt and his I would like to thank willingness to use his blanket in my experiments. @deanmalmgren | bit.ly/design-data
  16. 16. informal conversation to stated goals mostly bad ideas, but a few good ones @deanmalmgren | bit.ly/design-data
  17. 17. concept sketch comparisons qualitative a/b testing @deanmalmgren | bit.ly/design-data
  18. 18. concept sketch comparisons qualitative a/b testing @deanmalmgren | bit.ly/design-data
  19. 19. concept sketch comparisons qualitative a/b testing @deanmalmgren | bit.ly/design-data
  20. 20. concept sketch comparisons qualitative a/b testing @deanmalmgren | bit.ly/design-data
  21. 21. concept sketch comparisons qualitative a/b testing @deanmalmgren | bit.ly/design-data
  22. 22. concept sketch comparisons qualitative a/b testing @deanmalmgren | bit.ly/design-data
  23. 23. concept sketch comparisons qualitative a/b testing @deanmalmgren | bit.ly/design-data
  24. 24. concept sketch comparisons qualitative a/b testing search engine with relevance metrics demographics human readable expertise summary @deanmalmgren | bit.ly/design-data
  25. 25. from sketch to blue print add detail to get feedback (while building) @deanmalmgren | bit.ly/design-data
  26. 26. from sketch to blue print add detail to get feedback (while building) @deanmalmgren | bit.ly/design-data
  27. 27. from sketch to blue print add detail to get feedback (while building) @deanmalmgren | bit.ly/design-data
  28. 28. prototype iterations faux first; KISS; build for feedback @deanmalmgren | bit.ly/design-data
  29. 29. prototype iterations faux first; KISS; build for feedback @deanmalmgren | bit.ly/design-data
  30. 30. prototype iterations faux first; KISS; build for feedback @deanmalmgren | bit.ly/design-data
  31. 31. prototype iterations faux first; KISS; build for feedback @deanmalmgren | bit.ly/design-data
  32. 32. tips for designing with data problem lost in translation generate hypotheses takes a long time to collect data, analyze, and build visualization evaluate feedback 1-4 week iterations build prototype proof is in the pudding @deanmalmgren | bit.ly/design-data
  33. 33. solve ambiguous problems with an iterative approach http://bit.ly/design-data ! @deanmalmgren dean.malmgren@datascopeanalytics.com

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