Published on March 14, 2014
WELCOME Dean (@deanmalmgren) Mike (@mstringer) Laurie (@laurieskelly)
INTERVIEW EXPLORE SYNTHESIZE SKETCH OBSERVE PROTOTYPE FORM GROUPS
INTERVIEW listen carefully be thoughtful, ask why, dig deep empathy is key 10 MINUTES
INTERVIEW WHEN DATA IS INVOLVED • Learn about the nuances of a problem • What makes this relevant for humans? • Who uses it and why?
EXPLORE build on others thoughts prefer radical ideas one mouth at a time 20 MINUTES
EXPLORE WHEN DATA IS INVOLVED • Have the attitude that “anything is possible (eventually)” • Don’t focus too much on the details of the data or analysis • Speak the language of the problem, not the solution
SYNTHESIZE clump post-its in groups stars will force a decision mistakes are OK 15 MINUTES
SYNTHESIZE WHEN DATA IS INVOLVED • Tweak or discard clearly infeasible ideas • But still focus on usefulness, not feasibility
SKETCH sketch out your concepts ignore distracting details ugly is just !ine 20 MINUTES
SKETCH WHEN DATA IS INVOLVED • Usually sketch many times before writing any code • Make sure concept addresses one use case well • Use finer tipped markers, pens, and pencils for more detail • Build even more refined wireframes with inkscape/photoshop • Keep using the language of the problem owners, not nerd speak.
OBSERVE observe carefully don’t defend, they’re helping you empathy is key 10 MINUTES
OBSERVE • Understand which parts of concept are useful or not (and why!) • Ask for suggestions and questions WHEN DATA IS INVOLVED
PROTOTYPE make your concept real it’s not the !inished product build for more feedback 40 MINUTES
PROTOTYPE WHEN DATA IS INVOLVED • This involves getting data, doing some analysis, and presenting results • Short iteration cycle forces you to focus on essential parts • Important thing is to start building trust with end users • The details of feasibility come up here • It’s OK to fail; you’ve got lots of good ideas on the backburner
THANKS Dean (@deanmalmgren) Mike (@mstringer) Laurie (@laurieskelly)
Laurie Skelly is a Data Scientist at Chicago-based data consulting firm Datascope, and a curriculum developer and instructor for the Data Science bootcamp ...
Strata preview 2014: Design thinking for dummies (data scientists) from Dean Malmgren Data scientists often face ambiguous challenges and, as a group ...
This talk describes a Design Thinking methodology for tackling Data Science projects. ... Design Thinking for Data Scientists George Roumeliotis.
I gave a talk on Design Thinking for Data Scientists at the O'Reilly Strata Conference in February 2015.
Data Everywhere: Making Data Work ... how to apply design thinking to your data and identify ... Design Thinking for Data Scientists ...
Design Thinking for Dummies (Data Scientists) - Michael Stringer, Dean Malmgren, and Laurie Skelly - Part 1
Please click button to get data science for dummies ... doesn't take a data scientist to ... up data warehouse designs Understand the ...
What Is Data Science? ... Data Scientists don’t just present data, data scientists present data with an intelligence awareness of the consequences of ...