Nikhil Arora, Back to the Roots , @backtotheroots Alejandro Velez, Back to the Roots , @backtotheroots Back to the Roots founders Alejandro Velez and Nikhil Arora share their journey from investment banking to mushroom farming and aquaponics. They reveal the lean principles they’ve learned along the way that led them to launch a new line of organic breakfast cereals into thousands of grocery stores and classrooms this year.

1. Lean Startup 201
Jonathan Bertfield & Adam Berk
November 16 th
, 2015
2015 Lean Startup Conference
Sponsored by:

2. Jonathan Bertfield
• 20 Years in Product
Management
• Consulting clients: Pearson Inc.,
Disney, Associated Press, News
Corp. Sesame Workshop,
Business Insider, American
Press Institute
• Coach at General Assembly
Enterprise, NYU Stern
Adam Berk
• What problem are you solving? I
help teams pick their riskiest
assumptions and run
experiments.
• Currently at Pearson with >>
• Founded a sharing economy site
with the opposite result of AirBnb

4. 201 agenda
1. Who’s here? Why?
2. What will I learn?
3. What is the Lean Startup & where did it
come from?
4. How and why does it work?
5. What should I do next? (go to Aubrey’s
WS!)

5. what will I learn?
Deep dive into riskiest assumptions,
hypotheses
Discussion of Topics:
• What is an MVP (what are some great examples?)
• What do I measure?
• What do I do with my learnings?
Exercise: list your assumptions and rank
them
Get INTO and THROUGH BML once!

6. Common Purpose
We share a vision for the kind of company
we want to create:
A company that continuously creates
new sources of growth.
A company that actually creates value for
customers.

7. recap from 101
1. Quickly build products that matter
2. Recognize your assumptions (what you
know vs. what you don’t)
3. Test assumptions early and often
4. Don’t spend time and money building
the wrong things

8. teaser for 301
1. Get out your bunsen burners because you are going
to run a REAL experiment
2. Aubrey Smith worked directly with Eric Ries
integrating Lean Startup at GE, you don’t want to
miss her workshop!
3. Advanced topics like innovation accounting,
governance, regulated markets

9. we believe that you…
1. have read the book
2. believe that LS is “at least worth
considering”
3. have run an experiment or thought about
it in your lifetime
4. want to run more experiments with your
team

10. we believe you
will leave here with...
• An “intermediate level understanding” of
the current state of Lean Startup thinking
• An understanding of what to test
• An introduction to how to run experiments
THE CONFIDENCE TO GET IN (AND
THROUGH) THE LOOP

11. we promise...
● practical
● no jargon
● honesty
If you promise
● to trust us the first time, test us the second
time
● respect your peers
● participate fully in the exercises without fear
of...

12. what is a startup?
“A human institution designed to create a
new product or service under conditions of
extreme uncertainty. “
- Eric Ries
author, The Lean Startup

13. A method to systematically address
uncertainty through rapid iteration and market
learning.
what is the Lean Startup?

14. what is the Lean Startup?
History
Terminology / Definitions
Application / Applicability

15. simple history of Lean Startup
• Edwards Deming
• Lean Manufacturing - Toyota Production System
• Agile Software Development
• Customer Development - Steve Blank
• Lean Startup - Eric Ries
• Business Model Canvas - Osterwalder
• Lean Startup Community

16. ENTERPRISE
STARTUPS

18. Three Key Areas to Discuss
History
Terminology / Definitions
Application / Applicability
what is the Lean Startup?

19. Terminology / Definitions
• Entrepreneurs
• Startups
• Uncertainty (Product / Market / Model)
• Minimum Viable Product / Pre MVP
• Experiments
○ Assumptions
○ Hypotheses
○ metrics, vanity metrics, customer development
• Validated Learning (how to do test and measure the
right things)
• Pivots
what is the Lean Startup?

20. scientific methodRoger Bacon (1214 - 1284) is credited as the first scholar to promote inductive reasoning as part of the scientific
method.
1. Identify problems to generate ideas
2. Identify and prioritize the underlying
assumptions behind those ideas
3. Generate hypotheses and predictions
4. Define and deliver tests that expose
opportunities for learning
5. Use resulting data to inform activity

21. Attribution: CC George Thomas

23. Attribution: CC bixentro

24. what kinds of uncertainty?
Technical / product
Can we build this?
Customer / market
If we build this, will people use/buy it?
Business model
Once we build this, can we find a way to make money from it?

25. ● Technical / product
○ TESLA BATTERY, SOLAR, SOME STUFF THAT
AUBREY WILL TALK ABOUT IN 301
● Customer / market
○ YOUR IDEA (99% of the time)
● Business model
○ GROUPON, HOMEJOY
what kinds of uncertainty?

27. @FAKEGRIMLOCK - follow HIM, HER, IT? -- it’s
BRILLIANT

29. Minimum Viable Product
Translate your critical assumptions into an experiment:
1. Isolate critical assumptions for testing
2. Prioritize assumptions for testing
3. Draft your hypothesis to be tested
4. Build an experiment
5. Measure the results
6. Collect the data and learning in a systematic
Validated Learning
using scientific principles

30. High Risk
Low Risk
UnknownKnown

31. Assumptions: prioritization
Why?
● Focuses you, your employees
● Draw line in the sand
● Introduces accountability
● Saves time
● Introduces “learning” culture
How
● most unknown thing that will kill the idea,
democratic, random?

32. Assumptions: @ AirBnb

33. Assumptions: Expert Tip
1. Do this as a team
Spend 1-3 days listing, prioritizing your critical
assumptions as a team
2. Get on the same page
Agree on what is most critical to test, how to test it
and when you will meet next to discuss the results (2,
4, 6 weeks)
3. Track everything
Assign one person in charge of collating & tracking
learning in an excel spreadsheet

34. scientific method
1. Identify problems to generate ideas
2. Identify and prioritize the underlying
assumptions behind those ideas
3. Generate hypotheses and predictions
4. Define and deliver tests that expose
opportunities for learning
5. Use resulting data to inform activity

35. components of an example
hypothesis
I believe [target market/customer type]
will [do this action / use this solution]
[at this level/frequency]
for [this reason]. (by this date)

36. how does it work?
Three Key Areas to Discuss
History
Terminology / Definitions
Application / Applicability

37. scientific method
1. Identify problems to generate ideas
2. Identify and prioritize the underlying
assumptions behind those ideas
3. Generate hypotheses and predictions
4. Define and deliver tests that expose
opportunities for learning (&PROOF)
5. Use resulting data to inform activity

38. Minimum Viable Product (MVP)
Experiment that helps you validate (or
invalidate) hypotheses about the value or
growth potential for a new product
An MVP helps you answer a specific question
about one of your assumptions (as fast as
possible and helps you understand the WHY)

39. MVP Pearson case study
Learn Build
Measure

40. Learn Build
Measure
MVP Pearson case study

41. scientific method
1. Identify problems to generate ideas
2. Identify and prioritize the underlying
assumptions behind those ideas
3. Generate hypotheses and predictions
4. Define and deliver tests that expose
opportunities for learning
5. Use resulting data to inform activity

42. measure results
What knowledge are you looking to gain?
LEARN or PROVE
What you are going to do with the knowledge
when you get it?
START THE LOOP AGAIN BASED ON NEW
EVIDENCE, NEW LEARNINGS, NEW
PROOF!!!

43. why does it work?

44. why does it work?
(less luck more skill)

46. Path to Success

47. The ability to LEARN faster
than your competition may be
the only sustainable
competitive advantage.
Arie de Geus

48. Questions?
Phil Dillard
Lean Startup Trainer
415-894-5297
Phil@LeanStartup.co
Heather McGough
Co-Founder, Lean Startup Company
(415) 830-2479
Heather@LeanStartup.co