design thinking for dummies (data scientists) tuesday, february 11, 9:00 a.m. @deanmalmgren @mstringer @laurieskelly 2014 february strata preview

data scientists thrive with ambiguity solve for x project evolution x=5+2 @deanmalmgren | bit.ly/design-data

data scientists thrive with ambiguity solve for x Ax=b project evolution x=5+2 @deanmalmgren | bit.ly/design-data

data scientists thrive with ambiguity solve for x Ax=b project evolution x=5+2 optimize Ax=b subject to f(x) > 0 @deanmalmgren | bit.ly/design-data

data scientists thrive with ambiguity solve for x Ax=b optimize f(x) project evolution x=5+2 optimize Ax=b subject to f(x) > 0 @deanmalmgren | bit.ly/design-data

data scientists thrive with ambiguity solve for x Ax=b optimize f(x) optimize our protability project evolution x=5+2 optimize Ax=b subject to f(x) > 0 @deanmalmgren | bit.ly/design-data

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 how many? what kinds of trees? move old trees? replace old trees? @deanmalmgren | bit.ly/design-data

origins of ambiguity unclear problems identify the best locations to plant new trees aesthetically pleasing? maximize growth? increase folliage? offset CO2 emissions? how many? what kinds of trees? move old trees? replace old trees? @deanmalmgren | bit.ly/design-data

design process is used everywhere anticipate failure generate hypotheses evaluate feedback 1-4 week iterations build prototype @deanmalmgren | bit.ly/design-data

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

design and data science challenges in practice problem lost in translation evaluate feedback generate hypotheses 1-4 week iterations build prototype @deanmalmgren | bit.ly/design-data

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 @deanmalmgren | bit.ly/design-data

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

solve ambiguous problems with an iterative approach http://bit.ly/design-data ! @deanmalmgren dean.malmgren@datascopeanalytics.com