talk given to "Columbia startup teams including 2016 CVC winners, Ignition Grant winners, TFP fellows, and ASCENT fellows" as part of a mini-bootcamp for founders at columbia's engineering school 2016-05-24

1. lean + design thinking
in building data
products
chris wiggins
2016-05-24
associate prof @ columbia
chief data scientist @ nyt
cofounder @ hackNY

2. …a good definition of a data product is a product that
facilitates an end goal through the use of data.
Before investing in a big effort, you need to answer one
simple question: Does anyone want or need your product?
…start with something simple that lets you determine whether
there are any customers…It doesn’t have to be a great
solution; it just has to be good enough to let you know
whether it’s worth going further (e.g., a minimum viable
product).

3. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/

4. recommendation as predictive modeling
bit.ly/AlexCTM

5. (actually ML, shhhh…)
h/t michael littman

6. (actually ML, shhhh…)
h/t michael littman
(unsupervised
learning)
(supervised
learning)
(reinforcement
learning)
(generative
modeling)

7. optimization & prediction, e.g.,
(some models)
(somemoneys)
“newsvendor problem,” literally (+prediction+experiment)

8. prescriptive modeling, e.g,
cf. niemanlab.org Aug 13, 2015

9. prescriptive modeling, e.g,
cf. niemanlab.org Aug 13, 2015

10. NB: data-informed, not data-driven
cf. niemanlab.org Aug 13, 2015

11. …a good definition of a data product is a product that
facilitates an end goal through the use of data.
Before investing in a big effort, you need to answer one
simple question: Does anyone want or need your product?
…start with something simple that lets you determine whether
there are any customers…It doesn’t have to be a great
solution; it just has to be good enough to let you know
whether it’s worth going further (e.g., a minimum viable
product).

12. what worked?
1. customer interviews
2. pain-driven development
3. actual science *with customer iteration
4. ops includes engagement ops

13. actual science *with customer iteration
1. mockup*
2. develop method
3. validate method*
4. deploy*
5. ops*
http://www.r-bloggers.com/lessons-learned-from-developing-a-data-product/

14. actual science *with customer iteration
1. mockup*
2. develop method
3. validate method*
4. deploy*
5. ops*

15. actual science *with customer iteration
1. mockup*
2. develop method
3. validate method*
4. deploy*
5. ops*
http://messymatters.com/ai-plus-ui/

16. ops includes engagement ops:
1. method working
2. infra working
3. integrating into process
1. quantitative monitors
2. qualitative monitors

17. ops: quantifying, optimizing, iterating
1. online: Google Analytics (“GA”: $0)
2. experiments: GA, Optimizely
3. surveys! IRL or surveymonkey ($0)
4. buying a market:
1. Google (search),
2. Facebook (feed),
3. (marketing…)

18. more info: free tools (e.g., GOOG)

19. more info: paid tools (e.g., GOOG & FB)

20. more info: paid tools (e.g., GOOG & FB)

21. more info: paid tools (e.g., GOOG & FB)
medium.com/@lydiapolgreen
2016-05-13

22. 1. customer interviews
2. pain-driven development
3. actual science *with customer iteration
1. mockup*
2. develop method
3. validate method*
4. deploy*
5. ops*
4. ops includes engagement ops
1. method working
2. infra working
3. integrating into process
1. quantitative monitors
2. qualitative monitors

23. what worked? (my subjective framework)
1. customer interviews
2. pain-driven development
3. actual science *with customer iteration
4. ops includes engagement ops

24. simpler frameworks
1. “lean”
2. design thinking

25. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/

26. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/
defining “lean”
“an innovation method for startup
companies that claims that the most
efficient innovation is the one for
which there is an actual demand by the
users”
Design Thinking vs. Lean Startup, 2016

27. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/
defining “lean”
Lean startup evolved from the “customer
development” method (Blank, 2006). The idea
behind these methods is, that in addition
to a process for “product development”, a
startup also needs a process for “customer
development” to find and understand the
customers. This leads to developing
solutions based on a user-centered approach
and adapting to customer needs.
Design Thinking vs. Lean Startup, 2016

28. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/
defining “lean”
Lean startup evolved from the “customer
development” method (Blank, 2006). The idea
behind these methods is, that in addition to
a process for “product development”, a
startup also needs a process for “customer
development” to find and understand the
customers. This leads to developing
solutions based on a user-centered approach
and adapting to customer needs.
Design Thinking vs. Lean Startup, 2016

29. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/
http://dschool.stanford.edu/dgift/
defining “design thinking”

30. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/
defining “lean”
Lean startup evolved from the “customer
development” method (Blank, 2006). The idea
behind these methods is, that in addition to
a process for “product development”, a
startup also needs a process for “customer
development” to find and understand the
customers. This leads to developing
solutions based on a user-centered approach
and adapting to customer needs.
Design Thinking vs. Lean Startup, 2016

31. https://steveblank.com/2014/07/30/driving-corporate-innovation-design-thinking-customer-development/
in common:
1. discovery oriented approach
2. learning as unit of understanding
3. focus on customers needs,
- not biz plan
- not your tech
Design Thinking vs. Lean Startup, 2016

32. lean + design thinking
in building data
products
chris wiggins
2016-05-24
associate prof @ columbia
chief data scientist @ nyt
cofounder @ hackNY