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6 Myths About DATA & DESIGN @changesciences changesciences.com

Myths About Designing with Data

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Page 1: Myths About Designing with Data

6 Myths About

DATA  &    DESIGN  

@changesciences

changesciences.com

Page 2: Myths About Designing with Data

1  DATA  =  NUMBERS  m

yth

Page 3: Myths About Designing with Data

Think of it like  ARCHEOLOGY  

Page 4: Myths About Designing with Data

It’s incomplete TRACES  

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…about PEOPLE  

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2  DATA  =  OBJECTIVE  TRUTH  myt

h

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Big  data  can  have  SIGNAL  BIAS  

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Big  data  can  have  ALGORITHMIC  BIAS  

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Be  a  bit  Bayesian  –  Updates beliefs –  Iterative –  Incorporates multiple sources –  Yes, and... –  Never 100%

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DATA  WITH  A  SOUL  Don’t collect it without purpose Use only what is needed Use data with empathy

 

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3  BIGGER  =  BETTER  myt

h

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BIG  DATA   THICK  DATA  

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Big  Data  •  What, where, when, how •  Multi-structured •  Collected by machines •  Broad •  Behaviors & actions of many people •  Collected as people do what they do •  People are not highly aware of data

being collected •  Analysis uses statistical methods

                     

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ü  Transactional data ü Customer service logs ü Analytics ü A/B tests ü  Social media posts ü  Sensor data

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Li:le  Data  •  It’s big data for one •  Focused on personal goals •  Individuals grant access to it,

rather than companies

                     

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Thick  Data  •  How and why •  Description •  Collected by people •  In-depth •  Behaviors, actions, emotions,

intentions, motivations of a few •  Collected as part of a study •  People are highly aware of data

being collected •  Analysis includes developing

codes, summaries, and themes                

   

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ü  Usability tests ü Contextual research ü  Interviews ü  Diaries ü Any study

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Strive for BALANCE  

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4  DATA  IS  FOR  MANAGERS  

myt

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poverty rainfall global happiness copyright value culture fit

attitudes employee performance DESIGN automobile safety

emotion economic growth engagement size of an atom corruption

healthcare outcomes learning intelligence emotional intelligence

potential output social media ROI risk dolphin population love

innovation national security reputation public influence

customer satisfaction team productivity violence in households

cooperation air pollution asset value of advertising trust pH

length of Saturn’s day online readership stress level accountability

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MEASURE  WITH  MEANING  Personal well-being Collective well-being Markets and money

 

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5  DATA  KILLS  INNOVATION  myt

h

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The key is  PAIRING  

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Data & DISCOVERY  

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Public datasets Interviews

Behavioral analytics Observations

Social media data Lean research

Competitive data Ideation

DISCOVERY  PAIRINGS  

Emotional analytics Diaries

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Data & IMPROVING  

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A/B tests Usability tests

Surveys Intercept interviews

Customer service data Interviews

Analytics Usability tests

IMPROVEMENT  PAIRINGS  

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6  THERE  IS  ONE  RIGHT  WAY  

myt

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THERE  IS  NO  PERFECT  METHOD  

 

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Decide on MEANINGFUL  MEASURES  

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Choose the right SIGNALS  

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Be sensitive to COMPLEXITY  

Page 33: Myths About Designing with Data

changesciences.com  @changesciences