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

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@deanmalmgren @DsAtweet 2014 february norc solve for ambiguity what the data literate can learn from the design process

description

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.

Transcript of Solving for ambiguity: what the data literate can learn from the design process

Page 1: Solving for ambiguity: what the data literate can learn from the design process

@deanmalmgren @DsAtweet

2014 february norc

solve for ambiguitywhat the data literate can learn from the design process

Page 2: Solving for ambiguity: what the data literate can learn from the design process

data scientists thrive with ambiguitysolve for x

x = 5 + 2

proj

ect e

volu

tion

A x = b optimize f(x)

optimize A x = b

subject to f(x) > 0

optimize “our profitability”

@deanmalmgren | bit.ly/design-data

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origins of ambiguitymany feasible approaches

@deanmalmgren | bit.ly/design-data

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origins of ambiguityunclear problems

@deanmalmgren | bit.ly/design-data

identify the best locations to plant new trees

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origins of ambiguityunclear problems

identify the best locations to plant new treeshow many?

what kinds of trees? move old trees?

replace old trees?

aesthetically pleasing? maximize growth? increase foliage? offset CO2 emissions?

@deanmalmgren | bit.ly/design-data

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@deanmalmgren | bit.ly/design-data

generate hypotheses

build prototype

evaluate feedback

“design process” is used everywhereanticipate failure

1-4 week iterations

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@deanmalmgren | bit.ly/design-data

generate hypotheses

build prototype

evaluate feedback

surveys, interviews, focus groups split testing, A/B testing QA; requirements churn

personas, scenarios, use cases business/product requirements story/user cards

build device prototypes minimum viable product write code

human-centered design lean startup agile programming

“design process” is used everywhereanticipate failure

1-4 week iterations

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@deanmalmgren | bit.ly/design-data

generate hypotheses

build prototype

evaluate feedback

proof is in the pudding

problem lost in translation

takes a long time to collect data, analyze, and build visualization

design and data sciencechallenges in practice

1-4 week iterations

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@deanmalmgren | bit.ly/design-data

a project always starts with…

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@deanmalmgren | bit.ly/design-data

a project always starts with…

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@deanmalmgren | bit.ly/design-data

a project always starts with…

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@deanmalmgren | bit.ly/design-data

a project always starts with…

Kathie was promoted

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@deanmalmgren | bit.ly/design-data

informal conversation to stated goalsmostly bad ideas, but a few good ones

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@deanmalmgren | bit.ly/design-data

mostly bad ideas, but a few good ones

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 Patty for her support on studying

Lorem Ipsum as well as the infinite wisdom of Linus van Pelt and his willingness to use his blanket in my experiments.

informal conversation to stated goals

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@deanmalmgren | bit.ly/design-data

mostly bad ideas, but a few good ones

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 Patty for her support on studying

Lorem Ipsum as well as the infinite wisdom of Linus van Pelt and his willingness to use his blanket in my experiments.

informal conversation to stated goals

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@deanmalmgren | bit.ly/design-data

mostly bad ideas, but a few good onesinformal conversation to stated goals

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@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

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@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

Page 19: Solving for ambiguity: what the data literate can learn from the design process

@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

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@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

Page 21: Solving for ambiguity: what the data literate can learn from the design process

@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

Page 22: Solving for ambiguity: what the data literate can learn from the design process

@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

Page 23: Solving for ambiguity: what the data literate can learn from the design process

@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

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@deanmalmgren | bit.ly/design-data

concept sketch comparisonsqualitative a/b testing

search engine with relevance metrics

demographics human readable expertise summary

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@deanmalmgren | bit.ly/design-data

from sketch to blue printadd detail to get feedback (while building)

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@deanmalmgren | bit.ly/design-data

from sketch to blue printadd detail to get feedback (while building)

Page 27: Solving for ambiguity: what the data literate can learn from the design process

@deanmalmgren | bit.ly/design-data

from sketch to blue printadd detail to get feedback (while building)

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@deanmalmgren | bit.ly/design-data

prototype iterationsfaux first; KISS; build for feedback

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@deanmalmgren | bit.ly/design-data

prototype iterationsfaux first; KISS; build for feedback

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@deanmalmgren | bit.ly/design-data

prototype iterationsfaux first; KISS; build for feedback

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@deanmalmgren | bit.ly/design-data

prototype iterationsfaux first; KISS; build for feedback

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@deanmalmgren | bit.ly/design-data

generate hypotheses

build prototype

evaluate feedback

proof is in the pudding

problem lost in translation

takes a long time to collect data, analyze, and build visualization

tips for designing with data

1-4 week iterations

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http://bit.ly/design-data !

@deanmalmgren [email protected]

solve ambiguous problems with an iterative approach