Innovation at 50x 031616

Innovation at 50x
Steve Blank
@sgblank
www.steveblank.com
03/16/16

Innovation ≠ Incubator
Innovation ≠ Accelerator
Innovation ≠ Startup
Innovation ≠ Lean Anything
Innovation ≠ Open
Innovation ≠ Reorganization

Innovation ≠ Café’s
These are all physical
places to do innovation

Innovation ≠ Café’s
These are all physical places
to do innovation
Having them does not
guarantee any innovation
will happen

Innovation Development
• Places:
– R&D, Engineering, Incubators, Accelerators,
Hackathons, Open Innovation, etc.
• Methodology:
– Waterfall, Agile, Lean
• Pedagogy:
– Lean LaunchPad/I-Corps, Case-studies, Mentors
• Metrics:
– KPI’s, StateGate®, ECV, Pivots, IRL, TRL, …
• Funding
– VC, Corporate VC, M&A, etc.

Innovation Development
• Places:
– R&D, Engineering, Incubators, Accelerators,
Hackathons, Open Innovation, etc.
• Methodology:
– Waterfall, Agile, Lean
• Pedagogy:
– Lean LaunchPad/I-Corps, Case-studies, Mentors
• Metrics:
– KPI’s, StateGate®, ECV, Pivots, IRL, TRL,…
• Funding
– VC, Corporate VC, M&A, Incremental, etc.

Innovation Is?
Satisfying users current or future wants/needs
by turning an idea into a product or service

Innovation Is?
Satisfying users current or future wants/needs by
turning an idea into a product or service
with speed and urgency, using minimal resources
and costs

Innovation Succeeds
• Where there is a path to adoption
• When it fits into the overall mission and strategy
• Because it performs, has metrics, …
• It is managed as an innovation portfolio
• And has management support (the spirit of “yes”)

Continuous disruption requires
Continuous Innovation
Steve Blank

Continuous disruption requires
Steve Blank
what’s this mean?
∧

20th Century Corporate Lifecycle

21st Century Corporate Lifecycle

Continuous Innovation requires
new management tools
Steve Blank

Continuous Innovation requires
new management tools
Lean Innovation Management
Steve Blank

Why Lean Innovation Management?
10x the number of initiatives in
1/5 the amount of time
50x

Can You Create an Organization that
Executes and Innovates?

Can You Create an Organization that
Executes and Innovates?
It’s Called an
Ambidextrous Organization
Source: James March, Charles O’Reilly, Michael Tushman

An Ambidextrous organization
achieves breakthrough innovations

while relentlessly improving the
way they execute current business
model

while relentlessly improving the way
they execute current business model
and serve existing customers

Types of
Company Innovation
Steve Blank

Three Horizons of Innovation
Source: Baghai, Coley, White
Mature Business
our established capabilities
Rapidly Growing Business Emerging Business

Source: modified Baghai, Coley, White
our established capabilities

New Three Horizons of Innovation
Known
Unknown
Partially Known
Level of innovation is defined by whether
the business model is being executed, extended or explored!
Execute
Explore
Extend

Existing Business Model:
Process Innovation
Execute Core Mission
Known

Process Innovation
Execute
Known
Partially Known
New Opportunities via
Business Model Innovation
Extends Core Business

Process Innovation
Execute
Execute/Search
Known
Unknown
Partially known
New/Disruptive
Business Model
Explores

Capabilities/Risk Assessment
Existing Capabilities
Low Risk
Need New Capabilities
High Risk
Some Capabilities
Moderate Risk
Known
Unknown
Partially known

Innovation Allocation Across the Horizons
Known
Unknown
Partially known
60-70%
20-30%
5-10%

Return on Investment by Horizon
Known
Unknown
Partially known
ROI 1-3 years
• Improve
• Partner
• Acquire
ROI 4-6 years
• Extend
• Invest
• Partner
• Acquire
ROI 4-10 years
• Incubate
• Invent
• Invest
• Acquire
Evangelos Simoudis/Steve Blank

Process
Innovation
Product Mgmt Is the Current Process for
Horizon 1
Horizon 1
Extend the core
Product
Management
Known
Stakeholders
Use traditional methodologies for Horizon 1 projects
Steve Blank

Horizon 1: Roadmap Driven R&D
• Use product roadmap
• Success: use in next gen product
– With “better” performance than last gen
• Corporate competence: Predictable product improvement
• Assets: IP, Advanced design
Model$1:$Roadmap`Driven$
Example:$Processor$Roadmap$$
Features$$and$
Performance$
Target$of$2018?$
Source: Ikhlaq Sidhu, UC Berkeley

Horizon 1: Market/Customer Driven
• R&D decide their own projects with signals from:
– Pilot studies
– Business Unit or CTO priorities
– External: start-ups and academic
– Demo days or open interfaces to suppliers, customers,
universities
• Projects must be relevant to core competencies
• Success: is awareness, market perception, $’s+ profit
• Assets: IP, Advanced design, External Industry Leadership
Source: Ikhlaq Sidhu, UC Berkeley

Process
Innovation
Disruptive
Innovation
Continuous
Innovation
Lean Is the Process for
Horizon 2 & 3 Innovation
Horizon 1
Extend the core
Horizon 2
Horizon 3
Speed &
Urgency
Lean
Use Lean Methodologies for Horizon 2 and 3 projects
Steve Blank

Lean Innovation
Delivers Products and Services
that users want and need
in a fraction of the time

Lean = 3 parts
Business Model Canvas
Part 1
Customers
Channels
Customer
Relationships
Revenue Model
Value
Proposition
Activities
Resources
Partners
Costs
Source: Alexander Osterwalder- Business Model Generation

Business Model Canvas = hypotheses of how you
create and deliver value for the company and its
customers
Part 1
Customers
Channels
Customer
Relationships
Revenue Model
Value
Proposition
Activities
Resources
Partners
Costs

1. Frame Hypotheses
• Frame Hypotheses 

1. Frame Hypotheses
• Frame Hypotheses Business Model Canvas

2. Test Hypotheses
• Frame Hypotheses
• Test Hypotheses
Business Model
Customer Development


Customer Development is how you search for the model

Turning the Business Model Canvas Into Facts

9 Guesses
Guess Guess
Guess
Guess
Guess
Guess
Guess
GuessGuess
Customers
Channel
Customer
Relationships
Revenue Model

Customer Development is
Hypothesis Testing

3. Build Incrementally & Iteratively
• Frame Hypotheses
• Test Hypotheses
• Build the product
incrementally &
Iteratively
Business Model
Agile Engineering




The Minimum Viable Product (MVP)
• Smallest feature set that gets you the most …
- learning, feedback, failure, orders, …
- incremental and iterative
• It is not a prototype
• It is not a deployable version with the fewest features
• It is what enables a test of a hypothesis
• It may be a drawing, a slide, a wireframe, clickable
workflow, etc…

The Pivot
• Definition: A substantive change to one or more of the
business model canvas components
• Iteration without crisis
• Fast, agile and opportunistic
• Weeks and $100K

Pivot Cycle Time Matters
• Speed of cycle minimizes cash needs
• Minimum feature set speeds up cycle time
• Near instantaneous customer feedback drives feature set
Customer
Discovery
Customer
Validation
Company
Building
Customer
Creation
ExecutionSearch
Pivot

Part 1
Agile Engineering
+
Part 2
Part 3
Elements of Lean Startup

Lean Gets Theory
2003
Blank
Agile Engineering
2011
Ries
2010
Osterwalder
HBR Cover
2013

Lean Gets Practice
MS&E 297: “Hacking for Defense”: Solving National Security
issues with the Lean Launchpad
In a crisis, national security initiatives move at the speed of a startup yet in
peacetime they default to decades-long acquisition and procurement cycles. Startups
operate with continual speed and urgency 24/7. Over the last few years they’ve
learned how to be not only fast, but extremely efficient with resources and time using
lean startup methodologies.
In this class student teams will take actual national security problems and learn how
to apply “Lean Startup” principles, ("business model canvas," "customer
development," and "agile engineering”) to discover and validate customer needs and
to continually build iterative prototypes to test whether they understood the problem
and solution. Teams take a hands-on approach requiring close engagement with actual
military, Department of Defense and other government agency end-users.
Team applications required in February. Limited enrollment. Course builds on
concepts introduced in MS&E 477.
Terms: Spr | Units: 3-4 | Grading: Letter (ABCD/NP)
Instructors: Blank, S. (PI) ; Byers, T. (PI) ; Felter, J. (PI)
2015-2016 Spring
• MS&E 297 | 4 units | Class # 47395 | Section 01 | Grading: Letter (ABCD/NP) | LEC
• 03/28/2016 - 06/01/2016 - with Blank, S. (PI); Byers, T. (PI); Felter, J. (PI)
Lean LaunchPad
For Students
2011
1250+ teams
Taught in 75
Universities
760+ teams
Taught by 50
Universities
I-Corps
For SBIR/STTR
2012
I-Corps
For Life Sciences
2014
I-Corps
For NSA
2015
~250,000 on-line
students
Udacity.com

Lessons learned
after 130 interviews
Yegor Tkachenko,
MS
Marketing Analytics
Machine Learning
Eric Peter, CS & MBA
Consumer Insight Expert
Management Consulting
Scott Steinberg,
MBA
Marketing Growth Strategy
Karan Singhal, Undergrad
CS
Web Development
User Interface Design
Share&Tell

Share&Tell
Yegor Tkachenko,
MS
Marketing Analytics
Machine Learning
Eric Peter, CS &
MBA
Consumer Insight Expert
Scott Steinberg,
MBA
Marketing Growth Strategy
Karan Singhal,
Undergrad CS
Web Development
User Interface Design
Day 1 (Clarified)
We create a way for consumers to
make money by actively sharing
their behavioral data and
opinions.
Through this data, we help
companies unlock previously
unattainable insights.
Now
We help retailers and CPG
companies understand online
shopping behavior.
We do this by creating a platform
for people to donate their Amazon
shopping history
to raise money for charity.
130
Interviews
3,500+
Survey
responses

Cost Structure
Fixed - Infrastructure, servers, team of data scientists,
corporate sales force, project managers & analysts, product
& user experience development team
Variable - Payment to consumers for use of their data, profit-
sharing model (dividends) with consumers, consumer
service reps
Revenue Streams
1. Custom research studies
2. Per-feedback fees (surveys, video interviews, focus groups)
3. Sales of raw data / data with automated analytics on top
4. Subscriptions to the platform
Pricing based on sample size/type, data type/amount, number of questions,
feedback time
Key Resources
Key ActivitiesKey Partners Value Proposition Customer
Relationships
Channels
Business Canvas - Week 1
Customer
Segments
Consumers
• Millennials/students
• Lower income
consumers with
smartphones
• Existing research
participants
Enterprises
• Marketing agencies,
consulting
• Marketing
departments at large
companies
• Marketing
departments at non-
large CPG companies
• Panel acquisition, retention,
incentivization, quality control
• Automated seamless
insights extraction
• Data security
• Empowered customer
service (for consumer)
• Sales force, customer
service knowledgable about
market research design &
execution
• Historical granular data
• Automated platform for
seamless insights
extraction
• Expertise in market
research methodology,
execution, statistics
Consumers
• Profit sharing
• Targeted ads in line
with customer’s tastes
• Sense of empowerment
Enterprises
• Unique data,analysis
• Easy and fast way to do
it
Consumer
• Website
• Mobile app
Enterprise
• Direct web portal
• Resold through market
research agencies
• Custom consulting &
research design services
Consumers
• Getting paid for data that
has already been shared,
but from which individuals
are not profiting
• Provide sense of
empowerment and control
over data
• Offers a natural, effortless
way to share opinions
• Feel heard and that
opinion matters
Enterprises
• Linking real-behavior with
opinions (vs. stated
behavior)
• Ability to follow up with
consumer
• Faster turnaround
• Data API providers
• Data aggregators
• Marketing agencies
• Panel participants
blue = consumer
black = enterprise

What we thought: Enterprise VP blue = consumer
black = enterprise
Enterprise Value Proposition:
Replace traditional survey providers by:
● Linking real behavior with opinions (vs.
stated behavior)
● Ability to follow up with consumer
● Faster turnaround
Key
Resources
• Historical granular
data
• Automated
platform for
seamless insights
extraction
Demographics
● Age?
● Gender?
● ...
Behavior
● Where did you buy?
● What? How much?
● ...
Emotions / Feelings
● Why did you buy?
● What matters to you?
● ...
Survey
Surveys are based on
SELF REPORTED data

What we did: Talk to companies
who use surveys for market research
Hypothesis:
We can replace existing
panel vendors if we have
real behavioral data
(as opposed to self-reported
data)
What we did:
12 Customer Discovery
interviews with companies
that conduct market research
using surveys
Enterpris
e
Week 1-3

What we found: Not that much
pain with self-reported data...
“Self-reported data isn’t
great, but it’s directionally
good enough.”
“With real data, we’d get the
same insight as we do now, but
perhaps we’d be slightly more
confident.”
“In order to switch
vendors, you need to be
able to answer a question
we can’t answer today”
“We have to use [vendor] -
we have a long term
contract through our HQ."
Enterprise
Week 1-3

What we found: Not that much
pain with self-reported data...
“Self-reported data
isn’t great, but it’s
directionally good
enough.”
“With real data, we’d get
the same insight as we
do now, but perhaps
we’d be slightly more
confident.”
“In order to switch
vendors, you need
to be able to answer
a question we can’t
answer today”
“We have to use
[vendor] - we have a
long term contract
through our HQ."
Enterprise
Week 1-3
Adding behavioral data alone does
not make us 10x better.
We need to be able to answer a specific
question that marketers can’t answer
today

So, we focused on changing the value prop
to answer new questions for marketers
How should I
identify my
consumer target
(SMB Businesses)
How do I better
understand my
consumer target?
What is the path to
purchase for online
and omnichannel
shopping?
What are current online
shopping trends?
Customer Needs Identified through Customer Discovery:
Enterprise
Week 1-3

So, we focused on changing the value prop
to answer new questions for marketers
How should I
identify my
consumer target
(SMB Businesses)
How do I better
understand my
consumer target?
What is the path to
purchase for online
and omnichannel
shopping?
shopping trends?
Customer Needs Identified through Customer Discovery:
Enterprise
Week 1-3
Value Proposition
Enterprises
• Linking real-
behavior with
opinions (vs. stated
behavior)
• Ability to follow up
with consumer
• Faster turnaround
Value Proposition
Enterprises
• Identify target
consumers to
increase marketing
ROI
• Deeper and more
accurate behavioral
understanding of
consumer
segments
• Understand
online/omnichannel
path to purchase
• Understand online
market trends at
consumer level
Week 1 Week 3
✘

Cost Structure
Fixed - Infrastructure, servers, team of data scientists,
corporate sales force, project managers & analysts, product
& user experience development team
Variable - Payment to consumers for use of their data, profit-
sharing model (dividends) with consumers, consumer
service reps
Revenue Streams
2. Per-feedback fees (surveys, video interviews, focus groups)
3. Sales of raw data / data with automated analytics on top
4. Subscriptions to the platform
feedback time
Key Resources
Relationships
Channels
What we thought: Consumer VP
Customer
Segments
Consumers
• Millennials/students
• Lower income
consumers with
smartphones
participants
Enterprises
• Marketing agencies,
consulting
• Marketing departments
at large companies
• Marketing departments
at non-large CPG
companies
• Automated seamless insights
extraction
• Data security
• Empowered customer service
(for consumer)
• Sales force, customer service
knowledgable about market
research design & execution
seamless insights extraction
Consumers
• Profit sharing
• Targeted ads in line with
customer’s tastes
• Sense of empowerment
Enterprises
• Unique data,analysis
• Easy and fast way to do it
Consumer
• Website
• Mobile app
Enterprise
• Direct web portal
• Resold through market
research agencies
• Custom consulting &
research design services
Consumers
• Getting paid for data that
has already been shared, but
from which individuals are not
profiting
empowerment and control
over data
• Offers a natural, effortless
way to share opinions
• Feel heard and that opinion
matters
Enterprises
• Linking real-behavior with
opinions
• Ability to follow up with
consumer
- Faster turnaround
• Give additional context in
traditional surveys
blue = consumer
black = enterprise
Consumer Value Proposition
Hypothesis:
Get paid for your data
Feel in control of your data
Feel heard and that opinions matter
...and, that consumers are willing
to provide all these data types:
• Social media likes & posts
• Email purchase receipts
• Credit card purchase history
• Amazon.com purchase history
• GPS location history
• Web and search history

First consumer test
Hypothesis:
People will provide their data
and opinions for money
Tested through:
~25 Customer Discovery focused
consumer interviews
Consumer
Week 1-3

Experiment: Take an MVP on
an iPad to the mall
Consumer
Week 1-3

What we learned
Hypothesis:
People will provide their data
and opinions for money
Consumer
Week 1-3
Findings:
People will provide data and opinions for money, BUT
Only younger and poorer consumers were interested
Cash-based model had other problems too:
● Doesn’t support retention and engagement
● Misaligned incentives
● Not scalable to get to large # of consumers
Tested through:
~25 Customer Discovery focused
consumer interviews

As a result: What if
we offered equity instead of cash?
Solves all business needs!
● panel retention and engagement
● identity verification
● quality of data
Consumer
Week 4
Google Consumer Survey: n = 500

Oh Wait… Need to Isolate Variables
Always be skeptical of your data!
Consumers aren’t interested in concept of being a
partial owner - they cared about the extra cash!
Designing a good experiment just
saved us 49% of our equity...phew!
Consumer
Week 4

Value Proposition
Consumer:
• Getting paid for
data that has
already been
shared, but from
which individuals
are not profiting
empowerment and
control over data
• Offers a natural,
effortless way to
share opinions
• Feel heard and
that opinion matters
By Week 4, We Had No Idea What
Consumer Value Prop Should Be
Value Proposition
Consumer:
• Getting
compensated
for data that has
already been
shared
• Provide sense
of
empowerment,
control over
data
• Partial
ownership of
company
Week 1-4
Consumer
Week 1-4
Consumer:
• Control over
data
• ???
Value Proposition
Week 1 Week 3 Week 4

Let’s first focus on narrowing
down enterprise value prop to see
what data we need.

What we did: Customer
Validation!
How should I identify
my consumer target
(SMB Businesses)
How do I better
understand my
consumer target?
What is the path to
purchase for online and
omnichannel shopping?
shopping trends?
✘ ✘
Enterprise
Week 4
14 more enterprise interviews to (in)validate our
hypothesized value props and identify the most acute needs

“Great value prop guys, but I
challenge you - if you had to do
something tomorrow as an MVP,
what would it be? This is a LOT to
do!”
Note: Quote paraphrased, concept of “Big Idea” was likely referenced
Key learning: A startup can’t do everything. It needs to
do one thing well!
Enterprise
Week 4

Well, why not focus on data
that’s easiest to get?
Most
Sensitive
Least
Sensitive
Google Survey
Consumer
Week 5

And heard from companies that
Amazon data is big pain point
Enterprise
Week 5

As a result: An aha moment...
Share & Tell…
...helps better understand your target's online &
omnichannel shopping & purchasing behavior
• What is purchased on Amazon.com?
• What is my online/omni market share? Why?
• Where else does my target shop? Why?
• What does my target do before they buy? What
is their shopping path? Why?
• What products does my customer buy / not buy?
What do they buy with my product? Why?
...helps better understand your target's persona /
where to reach them
• What online behaviors (sites, apps, etc…)?
• What media consumption habits?
• What do they search for online?
• What activities, interests, hobbies?
• What demographics?
...provides ability to more directly and
narrowly communicate with your target
• Direct messaging / promos on S&T platform
• Better targeting on existing ad networks
Enterprise
Week 5-6

Cost Structure
Fixed - Infrastructure, servers, team of data scientists, corporate
sales force, project managers & analysts, product & user
experience development team
Variable - Payment/donations for use of their data, consumer
service reps
Revenue Streams
1. Subscriptions to insights / platform
2. Per-survey fees
4. Linking data to client databases
feedback time
Key Resources
Segments
Customer
Relationships
Channels
Resulting Business Canvas
Consumers
• Smartphone using
consumers who shop online
• Millennials
participants
• People who currently give to
charity
Enterprises
• Retail (traditional)
• Retail (e-commerce)
• CPG with online sales
• Automated seamless
insights extraction
• Data security
• Empowered customer
service (for consumer)
• Sales force, customer
service knowledgable about
market research design &
execution
seamless insights
extraction
Consumer
• Website
• Mobile app
Enterprise
• Direct web portal supported
by research-experience B2B
sales force
• Projects sold through
market research & strategy
firms
Consumers
• Get: Charities send invitations
• Get/Keep: Shopping discovery
+ targeted discounts app
• Keep: Reports / comparisons of
your data
Enterprises
• Get:partnership,telesales,PR
• Keep: Unique data, analysis
Consumers
• Feel good by donating data
to charity
• (potentially) Service to
discover, get discounts on,
and buy stuff online
Enterprises
• Understand purchasing
trends on Amazon by
demographic group
• Charities/non-profits
Enterprise
Week 5-6blue = consumer
black = enterprise
• Understand purchasing trends
on Amazon by demographic group
• Retail (traditional)
• Retail (e-commerce)
• CPG with online sales

As a result: Develop low-fi MVP
Enterprise
Week 5-6

Now, how do we incentivize
consumers to provide Amazon
data?
Consumer
Week 5

We identified a few possible
alternatives to cash...
Pay
cash
Provide a
valuable service
$5 / $10 cash
Donate your
data
(to benefit a
charity)
Receive
targeted
promotions
Personalized
product
recommenda
tions
✘
Had learned previously consumers more willing to
share data if they get some intrinsic value
Consumer
Week 5

What we did: 10+ Customer Discovery
interviews...and 2,000+ survey responses
Consumer
Week 5

What we found: “Donate your data”
best meets the business’s needs
Gets
Amazon
data?
Retention
/
engageme
nt? Quality? Large #? Outcome
$5 / $10
cash
✔ Cash is king! ✘ May be
transactional /
one-shot deal
✘ Limits to low
income
✔ ~>50%
interested
Kill for now or
use in combo
w/ donations
Donate
your data
✔ Interest in
‘doing good’
✔ Donation
implies opp to
ask for future
donation
✔ Consumer
leads verified
through charities
✔ ~27%
interested
Focus for
class; need to
understand
impact of bias
Targeted
promos
✘ Does not
solve major pain,
already available
✔ Creates clear
gain w. reason to
come back
✔ Can verify
respondent
behavior
✘ Quant test
running,
qualitatively poor
reaction
Test for “keep /
grow” insteadProduct
recs
✘ Limited
interest - does
not solve pain,
not 10X better
than others
✔ Creates clear
gain w. reason to
come back
-- Unclear if able
to verify
respondent
• Need 0.75% of TAM to register (1M / 150M)
• Of those interested, ~3% will register
• Implies >25% interested
Consumer
Week 5

What we found: Consumers
skeptical of donation scams
“I’d donate my Amazon
data to raise money for
charity X, but only if that
charity asked me too”
“I probably would not
donate to a random
startup unless I knew for
sure that they were legit”
Nonprofits should send out
communication asking
people to donate their data
Nonprofits are a customer
acquisition channel and a
new customer segment
Consumer
Week 5

As a result: 3-sided market
Consumer
Week 6

Value Proposition
Consumer:
• Control over data
• ???
Consumer:
• Feel good by
donating data to
charity
• Doesn’t cost
money to donate
Value Proposition
Week 3 Week 5
Resulting BMC changes (I)
Consumer:
• Millennials &
students
• Lower income
consumers with
smartphones
participants
Segment
Consumer:
• Millennials
• People who
donate to charity
Segment
Consumer
Week 6
✘
✘

Value Proposition
Non-Profit:
• A new revenue
stream
• A new way to
engage with donor
base
• A way to get
donations without
pushback
Value Proposition
Week 3 Week 5
Resulting BMC changes (II)
Segment
Non-Profit:
• All non-profits
Segment
Consumer
Week 6

Resulting BMC changes (III)
Consumer
Week 6
Consumer:
• Targeted ads in
line with customer’s
tastes
• Sense of
empowerment
Cust. Relationship
Consumer:
• Get: Charities
send invitations
Cust. Relationship
Need to test this
✘

eCommerce Data &
Insight Companies
Data aggregators
Online Donation
Tools and Platforms
Slice, Clavis,
Profiteero,
One Click
Retail,
Profiteero,
Return Path,
Paribus?
Data Wallet,
Datacoup, Infoscout,
Axciom, Experian,
LiveRamp, SuperFly
Razoo, CrowdRise,
Causes, Survey
Monkey, One Big Tweet,
GoodSearch,
AmazonSmile
Marketing research
agencies
TNS Qualitative, ,
Conifer Research,
Horowitz Research,
Nielsen, Kantar,
IPsos,
dunnhumby
Our Competitive
Set Has Evolved
too
Removed through pivots
Online Survey Tools
Traditional survey panels
Online qualitative research
Behavioral Consumer
Panels
(w/ or w/o surveys)
Nielsen, NPD, IRI,
LuthResearch,
VertoAnalytics,
RealityMine,
comScore
SHARE &
TELL
Consumer
Week 6

Nonprofits might not be the right
route
What we did:
Interviewed 10+
nonprofits
Tested email
campaign to 60
nonprofits to
gauge interest
What we learned:
● Only nonprofits who value
smaller donations (<$100)
from larger base of people
were interested in the
model
● Nonprofits are slow to make
decisions and risk-averse
So what?
Focus more efforts on
testing viability of direct to
consumer route.
Key hypothesis to test: Can
we build enough trust
through social media and
website?
Nonprofits
Week 7-9
Non-profits may
not be most
efficient
consumer
acquisition path.

What we did: Tested ‘direct to consumer’
using a high fidelity MVP...
https://www.datadoesgood.com
Consumer
Week 7-9

What we learned: ‘Direct to consumer’ might be a
viable route
Arrived to the
landing page
Clicked
‘donate now’
Logged in with
Facebook
Shared
Amazon data
Filled out
demographics
100%
~18%
~6%
~6%
~5%
~80%
~95%
~55%
Choose
a charity
~11%
~60%
25%
Consumer
Week 9

Cost Structure
Fixed - Infrastructure, servers, team of data scientists, corporate
sales force, project managers & analysts, product & user
experience development team
Variable - Payment/donations for use of their data, consumer
service reps
Revenue Streams
1. Subscriptions to insights / platform
2. Per-survey fees
4. Linking data to client databases
feedback time
Key Resources
Segments
Customer
Relationships
Channels
Consumers
• Online shoppers
• Current charity givers
• Millennials
participants
Enterprises
• Buyers at e-commerce
retailers
• Marketers at CPG with
online sales
Nonprofits??
• Hungry for donations and
values small donations from
large # of donors
• Private donations are main
revenue stream
• Donor acquisition??
• Donor retention and
engagement??
• Data quality control
• Data security and storage
• Automated analytics
• Custom analytics
• Sales force
• Legal
• Physical - workspace, servers
• Additional human (short-term) - Full-
stack software engineer, Database
architect, Security consultant, Legal
Consultant, Advisors/Industry Movers
(long-term) - Sales team, Analytics team,
Security team, Engineering team,
Advisors
• Intellectual - Trademarks, Contracts
with clients, Proprietary analytic tools,
Software copyright
• Financial - angel/venture funding
Consumers
• Website
• Mobile app
Enterprises
• Web portal supported by
B2B sales force
• Projects through market
research & strategy firms
Nonprofits??
• Web portal
Consumers
• Get: Social media campaigns &
charities send invitations
• Keep: Reports / comparisons of
your data
Enterprises
• Get:partnership,telesales,PR
• Keep: Unique data, analysis
Nonprofits??
• Get: telesales, PR
Consumers
• Feel good by donating data
to charity
• Donating is free & easy
Enterprises
• Understand purchasing
trends on Amazon by
demographic group.
brand preference
Nonprofits??
• A new revenue stream
• A new way to engage with
donor base
• A way to get donations
without pushback
Short Term:
• Charities/non-profits
• Nonprofit
hubs/associations
• Legal
• Other collectors of
online purchase history
Long Term
• E-commerce retailers
• Ad networks and
programmatic ad
buyers?
Final Business Model Canvas Week 10

So...what’s next...
We are going to continue working on this after
the class.
Can we gain traction with
consumers?
Several additional experiments we
want to run incorporating feedback
from our MVP.
● Facebook “nominations”
● Linking more directly to causes
● Many improvements to the MVP
Can we get a letter of intent from
any businesses?
We continue to hear companies say
they are interested and that this data
is valuable. Is one willing to sign a
non-binding letter of intent
First Priority Second Priority

What we learned: Refined value proposition
for enterprise...
Share & Tell…
...helps better understand your target's online &
omnichannel shopping & purchasing behavior
• What is purchased on Amazon.com?
• What is my online/omni market share? Why?
• Where else does my target shop? Why?
• What does my target do before they buy? What
is their shopping path? Why?
• What products does my customer buy / not buy?
What do they buy with my product? Why?
...helps better understand your target's persona /
where to reach them
• What online behaviors (sites, apps, etc…)?
• What media consumption habits?
• What do they search for online?
• What activities, interests, hobbies?
• What demographics?
...provides ability to more directly and
narrowly communicate with your target
• Direct messaging / promos on S&T platform
• Better targeting on existing ad networks
Enterprise
Week 4

...for 3 generic enterprise segments
Enterprise
Week 4
Retailers
Traditional
E-Commerce
1
2
CPG
With online sales
Without online sales
3

What is market research?
Comes in many forms...
1. Surveys to understand consumer opinions /
emotions
2. Data to understand market trends
Initial hypothesis:
“disrupt” survey-based market research

A quick primer:
How do surveys work?
What features do
my customers care
about?
1 Business asks a question about their customer
What does my
most valuable
customer look
like?
What drives
customer loyalty?

A quick primer:
2 Market research team writes a survey that will inform the answer
Demographics
● Age?
● Gender?
● ...
Behavior
● What? How much?
● ...
Emotions / Feelings
● What matters to
you?
Survey
5 - 10 minutes of
questions
10 - 15 minutes
of questions

A quick primer:
3 Survey sent to consumers through a ‘panel provider’
Demographics
● Age?
● Gender?
● ...
Behavior
● What? How much?
● ...
Emotions / Feelings
● ...
Survey
$ / person
Panel ProviderMarket Research team

Demographics
● Age?
● Gender?
● ...
Behavior
● What? How much?
● ...
Emotions / Feelings
● ...
Survey
A quick primer:
4 Consumers answer survey based on their memory
Self
reported
data

A quick primer:
5 Market research team analyzes data to develop an answer
Market Research team
Insight &
recommended
business action

Demographics
● Age?
● Gender?
● ...
Behavior
● What? How much?
● ...
Emotions / Feelings
● ...
Survey
...Where we thought we fit in
Why can’t this be based on actual
(vs. self reported) data?

Demographics
● Age?
● Gender?
● ...
Behavior
● What? How much?
● ...
Emotions / Feelings
● ...
Survey
...let’s be a “next gen” panel
provider that merges real data
with opinions

What data?
• Social media likes & posts
• Email purchase receipts
• Credit card purchase
history
• Amazon.com purchase
history
• GPS location history
• Web and search history
Opinions how?
• Record short video / audio
clips
• Take <5 min surveys
• Write reviews
• 1-1 text chats

Presenting
Share the key insights that led
to a decision or answer.
Don’t just share the answer
Example: Equity Idea
We learned a, b, & c...therefore we want to
do “x”
VS.
We want to do “x”. Here is some rationale
for why.
Preempt question the
audience might ask and prepare
responses.
Don’t bullshit if you don’t know
the answer. It’s okay to say need
time investigate it.
1 2

Group work
1. Set up regular recurring meetings at least twice a week
1. Carefully consider if the task is best performed by a group or by an individual
a. Everyone wants to participate in decision making, but it is often more efficient
if a single person completes 80% of the task and the group then finishes the
rest
1. If there is any tension, discuss it explicitly
1. Don’t take criticism of your ideas personally
1. Humor helps

Launchpad Methodology/Process
1. Applying the scientific method to business model is extremely useful
a. treating all ideas as hypotheses prevents attachment to bad ideas
i. also encourages rapid iteration to get to better ideas faster
b. using MVPs as tests of ideas rather than finished products avoids
wasting tons of development time
1. Interviews
a. what people initially say is not what they would actually do
i. need to push commitment to see what they actually do
b. interviews with experts are a quick way to get a lay of an industry
c. it’s surprisingly easy to get interviews with experts with a warm intro,
student status, and the purpose of learning as much as we can
d. need to clarify customer segment as early as possible to interview the
right people
i. early interviews should focus on figuring out who they are

Example 2:
National Science Foundation Team

Team 198
©Technology Review
An energy efficient, temperature sensitive
switchable window coating that blocks or
transmits heat
TAM
$172 Billion
Total Customer
Interviews – 105
Tech Video
Lessons Learned Video
http://youtu.be/RIR2SiQd1pk
http://youtu.be/8q8l5i3ISeU

Sarbajit Banerjee – Principal Investigator
• Associate Professor in Chemistry at University at Buffalo
Brian Schultz – Entrepreneurial Lead
• 2013 Ph. D. Candidate in Chemistry at the University at Buffalo
• Panasci Technology Entrepreneurship Competition Winner 2013
Martin Casstevens – Mentor
• Director of Directed Energy at the University at Buffalo
• Business Formation and Commercialization Manager – STOR
Team 198

Version 1
Window OEMs
Glass OEMs
Architectural Firms
Architectural Paint OEM
Fortune 50 Chip
Manufacturer
UB STOR – Incubator, IP,
Networking & Mentoring
NYSERDA - Directed
Energy
IP Assignment
R & D / Engineering
Strategic Partnering
End User Behavior
LEED & Energy-STAR Cert.
Increase Energy Savings
for End Users
Better Daylighting
LEED Points
Durability
Ease of Use & Integration
Higher Profit Margins
Faster Memory &
Computer PerformanceIP, Patents & Trade Secrets
Personnel
Nondilutive Support
Strong Visibility (MIT TR35)
UB & STOR Support
Raw Material Suppliers
Specially Engineered Equip.
OEM
Engineering Support
LEED & Energy-STAR Cert.
Tradeshows
Prototyping and Demos
Windows
Residential
Commercial
Auto
Interior Glass
Architectural Paints
Interior
Cool Roofing
Electronics
Cell Phones
Computers
Tablets
Flash Drives
OEM Distribution Chains
Contractors
Architects
Building Managers
Home owners
Retrofitting
Renovations
B2B Strategic Partnering with OEM
Personnel
Equipment, Tools, Raw Materials, Supplies, & Lab Space
Research & Development
Standardized Ratings
Proprietary Material Sales
IP Licensing
Engineering Services
Team 198

Market Size
Total Addressable Market – $172 Billion
• Total window and door sales worldwide
Serviceable Available Market – $29.5 Billion
• North American window
and door sales
Target Market – $6.6 Billion
• Green Windows & Doors
and Smart Glass Sales in
North America
Source - Custom Syracuse Report, Syracuse University New Technologies Law Center, 2013
Freedonia Research Report & bcc Research and Forecasting, 2010
Team 198
TAM
$172 Billion

First Hypotheses
Value Proposition – Energy Savings
• End users will pay for energy savings?
• Interview end users
Customer Segments
• Will OEMs partner with a startup on
new products?
• Interview OEMs and review past
behavior
Channels
• Are there any choke points between the OEM and end user?
• Investigate channels, i.e. architects, integrators, distributors
Revenue Model
• What premium will end user improved performance?
• Customer interviews
Team 198
Home Depot

Ecosystem – Version 1
SOLARMINDER
Materials
Eng. support
Glass Manufacturer
Integrator
Window Brands
- Retail outlets
- Homebuilders
- General contractors
HOMEOWNERS
- Const. Engineers
- Architects
BUILDING OWNERS
Residential Commercial
SOLARMINDER is a startup that seeks to license/partner with window manufacturers
to maximize (1) market penetration and (2) profit margins
Team 198

Customer Discovery
Team 198
LOWES
BLAINE Window Repair Thompson Creek Windows
Banner Glass Inc.

Customer Discovery
Team 198
Ryan McPhearson – Chief
Sustainability Officer
Albert Gilewicz – Associate Director
Utilities Operations
Ann Brozek – Sustainability Architect
Martha Bohm - Architect
Jennifer – Architect
Ray McGowan – Senior Program Manager NFRC
David Macleod – Principal at Cannon Design
Ron Foley – Head Engineer MaXPro Window Films
Joseph Murray – Ace Energy
Joanne – Sales at Old Castle Building Envelope
Bob – Artic Window Tinting
Woody Maggard – Former Ind.
Developer

Archetypes
Team 198
Customer OEM Archetypes
National – PPG, Guardian, ASG, MaXPro Window Films
International – CSR Australia, NSG (Pilkington)
Regional – Thompson Creek, Comfort Windows & Doors
Influencer Archetypes
Sustainability driven architects
Energy Consultants
Enduser Archetypes
High-end commercial buildings
often public
Commercial rehab and retrofits

Ecosystem – Version 3
SOLARMINDER
Materials
Eng. support
Window Manufacturer
Window Film Manufacturer
Glass Manufacturer
Retail outlets
Wholesale Distribution
Homebuilders
General contractors
Const. Engineers
Energy Consultants
Architects
INTEGRATORS
Residential
BRANDS
Sales Reps
HOMEOWNERS BUILDING OWNERS
INFLUENCERS
CHANNELS
NFRC Ratings Self Rate
CommercialDoE Energy-STAR
CUSTOMERS
END USERS
3rd Party Testing
Team 198

Advanced Energy Conference
Team 198
Jacobs Javits Center Exterior Curtain Wall
Advanced Energy Conference 2013 - NYC

Revenue Streams
SolarMINDER
Window Manufacturer ($65-75 per sq meter)
Window Film Manufacturer ($45-50 per sq meter)
Glass Manufacturer ($45-55 per sq meter)
Customer Segments
Sell Products
Activities
Eng. Services
$20-30 per sq meter
$150-200 per hour
Payments
Architects (5-8%)
MEP Engineers
Energy Modeling
Residential
BRANDS
Sales Reps
% commission
HOME OWNERS BUILDING OWNERS
Commercial
Glazing Int. ($70-85)
Architects (5-8%)
Energy Cons. (Contract)
Home Builders
Developers
Contractors (Bid??)
Architects (5-8%)
Retail Outlets (2-5%)
Wholesale Distribution
Contractors (Bid??)
Window Installers
Window Dist. ($65-75) Window Dist.
($70-75)

Strategic Partners
• National – PPG, Guardian, ASG, MaXPro Window Films
• International – CSR Australia, NSG (Pilkington)
• Regional – Thompson Creek, Comfort Windows & Doors
SolarMINDER
Sell Products
Eng. Services
Window Manufacturer
Window Film Manufacturer
Glass Manufacturer
Customer Segments
Potential Key Partners
Team 198

Competitive Threats
• Manufacturers of Low-E
• “Flip-of-a-switch”
(electrochromics)
• Metallic Low-E Plus
• Transitions
(photochromics)
• Lowering Energy Costs
Team 198
electrochromics

Next Steps
• Continue Strong Visibility
• Funding: SBIR, Angels, Venture Capital, NYSERDA
• Demo Projects: 3 sites identified
• Pilot testing with window film OEM
• Direct Engagement with OEMs
• Explore window curtain integrator in ecosystem
• NFRC accredited testing
Team 198

Team 198
©Technology Review
GO
Tech Video
Lessons Learned Video
http://youtu.be/RIR2SiQd1pk
http://youtu.be/8q8l5i3ISeU

Disruptive
Innovation
Continuous
Innovation
Lean Means Getting Out of Your Office
Horizon 2
Horizon 3
Speed &
Urgency
Lean
Steve Blank
• If you’re not talking to 100’s of customers, it’s not lean
• If you’re not building iterative and incremental minimum
viable products, it’s not lean

Managing Three Horizons of
Innovation - Current
Process Innovation
Execute
New/Disruptive
Business Model
Search
Execute/Search
Known
Unknown
Partially known
Lean Innovation Mgmt
Process
Mgmt

Managing Three Horizons of
Innovation - Goal
Execute
New/Disruptive
Business Model
Search
Execute/Search
Known
Unknown
Partially known
Lean Innovation Mgmt

NASA/DOD
Technology Readiness Level (TRL)
• Formal Way to assess project maturity
• Quantify Relative Risks
• Data Driven
• Adopted by NASA, DOD, FAA, ESA…

NASA/DOD Technology Readiness:
Levels 1 & 2
Basic Technology Research
• Basic principles observed
• Technology concept formulated
Concept

NASA/DOD Technology Readiness
Levels 3 & 4
Research to prove Feasibility
• Experimental proof of concept
• Breadboard validation in lab
Research
Concept

Levels 5 & 6
Demo Prototype
• Breadboard validation outside the building
• System demo in real-world
Research
Concept
Demo

Levels 7, 8, 9
Deployment
• System Development
• System deployed in real-world
Research
Concept
Demo

What Can We Do
With Customer Discovery Data?
The Investment Readiness Level

Investment Readiness Level
We can do the same
for new ventures

We can do the same
for new ventures
Emphasis is on data

• A Formal Way to Quantify Relative Risks
• Data Driven
• Analog to NASA/DOD
Technology Readiness Level (TRL)
• Use IRL as a way to establish immediate
funding increments

Investment Readiness:
Levels 1 & 2
Hypotheses
• Value Proposition summarized
• Canvas hypotheses articulated
Hypotheses

Levels 3 & 4
Problem / Solution Fit
• Problem Solution fit
• Low fidelity MVP
Hypotheses
Problem/Solution

Levels 5 & 6
Validate
• Product/Market fit
• Right side of canvas
Hypotheses
Problem/Solution
Product/Market fit

Levels 7 & 8
Validate
• Left side of canvas
Hypotheses
Problem/Solution
Product/Market fit

Levels 9
Metrics That Matter
Hypotheses
Problem/Solution
Product/Market fit
Left side of the canvas

Technology
Readiness Level
Problem/Solution
Hypotheses
Product/Market Fit
Validate
Right side of Canvas
Validate
Left side of Canvas
Metrics that Matter
Investment
Readiness Level

Horizon 1 Procedures
Meets a Horizon 3 Project
Steve Blank

Startups/New Corporate Initiatives
Start as Innovation Engines
New/Disruptive
Innovation
• Disruptive
• Business Model Innovation
• Better/faster/cheaper
• Innovation requires no restrictions
by plans, procedures or processes
• Success = finding a repeatable and
scalable business model
• Grows and scales
Steve Blank

Horizon 3
Horizon 3 Needs To Leave Home
Process
Innovation
Continuous
Innovation
Disruptive
Innovation
• Physically separate from
operating divisions
• Company Incubator, etc
• Their own plans, procedures, policies,
incentives and KPI’s
• They operate with speed and urgency
• Goal is to find a repeatable and
scalable mission model
Steve Blank

Success Creates “Debt”
Success creates
• Technical debt
• Organizational debt
• Refactoring “cleans up” debt
by restructuring it
Refactoring
Steve Blank
New/Disruptive
Innovation

Type of Innovation
Innovation Becomes Execution
Process
Execution
Disruptive
Innovation
• Success means scale
• Scale requires plans, procedures,
processes, incentives, KPI’s
• Innovation becomes execution
Refactoring
Group
Steve Blank
Continuous
Innovation

Horizon 3
Refactoring is an Integral Part of
Innovation
Process
Innovation
Disruptive
Innovation
• Horizon 3 takes shortcuts
• Technical shortcuts add up and
become what is called
Technical debt
• People/process shortcuts are
Organizational debt
• Refactoring “cleans up” debt by
restructuring it
• You need a process organization
dedicated to refactoring Horizon 3
projects
Refactoring
Group
Steve Blank
Horizon 1

Type of Innovation
Innovators Leave or Start New Initiatives
Process
Execution
Disruptive
Innovation
• Founders/early employees don’t
fit in execution organizations
• Short-sighted companies:
innovators leave
• Far-sighted companies: they
start the next cycle of innovation
Refactoring
Group
Steve Blank
Continuous
Innovation
Disruptive
Innovation

“Get to Yes”
Corporate support of Innovation in
All 3 Horizons
Process
Innovation
Refactoring
Group
Company
support orgs
Steve Blank
• Task Support Organizations to work inside Horizon 2/3
• Assign Finance, Legal, HR, etc.
• Job is helping all Horizon projects “get to yes”
• leverage existing assets and capabilities is critical
Disruptive
Innovation

Company Incentives & Goals
In support of Innovation in All 3 Horizons
Disruptive
Innovation
Steve Blank
• Companies operate on goals and incentives
• Incent mavericks, incent support, incent adoption
Process
Innovation
Refactoring
Group
Company
support orgs

Disruptive
Innovation
Steve Blank
• Company operates on goals and incentives
If there are no Horizon 2/3 incentives in the company then
there is no real commitment to innovation
Process
Innovation
Refactoring
Group
Company
support orgs

Disruptive
Innovation
Steve Blank
• Company operates on goals and incentives
If supporting Horizon 2/3 is not part of Company goals &
incentives then there is no real commitment to innovation
Process
Innovation
Refactoring
Group
Company
support orgs
Positive – Financial Awards, Performance
Bonuses, & Honorary Awards
Negative – You can lose product funding

Type of Innovation
Innovation Becomes Execution
Horizon 1 Adopts Horizon 2 & 3
Process
Execution
Steve Blank
Horizon 3
support orgs
Refactoring
Group
Continuous
Innovation
• Success means scale
• Scale requires plans, KPI’s
procedures, processes,
incentives
• Innovation becomes execution
Disruptive
Innovation
Horizon 2
Horizon 3
Horizon 1

Intrapreneurs are (Good) Rebels
Bad Rebels
Anger
Pessimist
Energy-sapping
Alienate
Problems
Vocalize Problems
Worry That
Point Fingers
Doubt
Social Loner
Assertions
Me-focused
Break Rules
Complain
Good Rebels
Passion
Optimist
Energy-generating
Attract
Possibilities
Socialize Opportunities
Wonder if
Pinpoint Causes
Believe
Social
Questions
Mission-focused
Change Rules
Create
Source: Carmen Medina www.rebelsatwork.com

Horizon 3 Protects Mavericks
Horizon 1 Fires Mavericks
• In Horizon 1
– Pains in the butt
– Always looking at something different
– Doesn’t get with the program
• In Horizon 3
– The head of your innovation project
– Invents your next capability

Shiny Objects
• Tech founder becomes enamored with new tech (shiny object)
• Company still dependent on Horizon 1 until new tech is adopted
Solution:
• Make sure that $’s, people, and infrastructure are in place to
cross the Tech Transfer “Valley of Death”

Leadership is Focused on Now
• Leadership managing for current business & quarterly earnings
• CEO and/or mgmt incentives all on current mission and goals
Solution:
• Align incentives
• Appoint a Corporate Chief Innovation Officer

Innovation Is a Buzzword
• Stop using it to describe everything
Solution:
• Use the Horizon 1, 2 & 3 metaphor

Failure is Career Retarding
• In a company a failed project is to be avoided at all costs
• In a Lean organization failure is part of the process
• Pivoting from a failure gets us learning

Bottleneck: The Intransigent Middle
Turning Go into No
• Top of the organization says, “Do it”
• Bottom of the organization
(innovators) ready to go
• Middle management kills it
– Actively
– Sabotage
– Benign Neglect
• Innovation programs die
Steve Blank
Innovation
Groups Ready
Middle Mgmt
Barrier
Executive
Buy-In
GO
NO

Why the Bottleneck?
• Threat
– Power, ownership, turf, prestige, pay
• Confused
– Job spec’s are still the same
– No training on how to support, participate
• No incentives to change behavior
• No penalty for ignoring it
Steve Blank

Sales Freezes Talking to Customers
• Sales says “no one can talk to our customers”
Solution:
• Customer Discovery is not pitching new products
Steve Blank

Engineering Is Not Talking to Customers
• Engineering believes innovation is about technology
Solution:
• Focus the organization on understanding customer problems
• Focus on solving current or future problems
Steve Blank

Towards New Horizons
Rethinking the Enterprise

Towards New Horizons
Rethinking the Enterprise
take best practices from startups and
apply it to the corporation

Hor
Known
Business Model
The Limits of Current Horizons
Horizon 1

189
Develop-
ment
Research
Horizon 1

Develop-
ment
Research
Business
Units
Horizon 1

Extend the
Business Model
Horizon 2

Develop-
ment
Research
Business
Units
Customers
Customers
Customers
Horizon 2

Develop-
ment
Research
Business
Units
Customers
Customers
Customers
• 90% of R&D dollars support existing products
• Research = adv development to support existing products
Horizon 1 & 2

Unknown
Business Model
Horizon 3

Develop-
ment
Research
Business
Units
Customers
Customers
Customers
Horizon 3

Copyright 2016 Evangelos Simoudis
Research
Development
Business
Units
In most companies, Horizon 3 research $’s are
eliminated or outsourced
e.g., university funding, government labs consortia
Today R&D’s mission Has Changed
Horizon 3

Develop-
ment
Research
Business
Units
Customers
Customers
Customers
Innovation
Outpost(s)
and
Inpost(s)
Solution = Innovation Outposts/Inposts

Innovation Outposts
Bus Dev
Strategy
& Corp
Dev
Corp VC
Ecosystem
Specific
R&D
Corp
Incubators
Steve Blank/Evangelous Simoudis
Innovation Outpost
• Standalone unit for Horizon 2 and 3 innovation
• May contain as needed:
• Corp VC
• Incubator
• Specific R&D
• Bus Development

Innovation Outposts
Bus Dev
Strategy
& Corp
Dev
Corp VC
Ecosystem
Specific
R&D
Corp
Incubators
Business Units
Business Units
Business Units
Technology
innovations
Business problems
& context
Innovation Outpost
Business model & Technology Innovations
Spin ins
New
Business Unit
Startups
Startups
Startups

Innovation Outposts
Bus Dev
Strategy
& Corp
Dev
Corp VC
Ecosystem
Specific
R&D
Corp
Incubators
Business Units
Business Units
Business Units
Technology
innovations
Business problems
& context
Innovation Outpost
Spin ins
New
Business Unit
• Outposts operate under many degrees of freedom
• e.g., investments, incubation
• Launches many experiments (investments, incubated teams)
inexpensively to test out innovation-related hypotheses

Innovation Outposts – Moonshot Support
Bus Dev
Strategy
& Corp
Dev
Corp VC
Ecosystem
Specific
R&D
Corp
Incubators
Business Units
Business Units
Business Units
Technology
innovations
Business problems
& context
Innovation Outpost
Business model & Technology Innovations
Spin ins
New
Business Unit
• Moonshot = large commitment of resources for a Horizon 3 goal
• Requires H1 & H3 collaboration

New
Unit
New
Unit
As new business units created by the Innovation Outpost grow,
they hire employees with different culture than that of the H1
corporate parent
H1 Corporation
Existing
BU
Existing
BU
Outposts Change the Culture
New Employees

New
Unit
New
Unit Existing
BU
H1 Corporation
Existing
BU
2) augmenting the H1 corporation
through their presence.
Outposts Change the Culture
Startups

Summary
• Lean Innovation Management is not about efficiency
and innovation
• It’s about developing the capabilities necessary to
offset competitors who may have equal or better
technologies
• It’s how to integrate, build, and reconfigure internal
and external competencies to address rapidly
changing environments
• It’s about survival in the 21st Century

Removing the Bottlenecks
• Prove that this can work
• Then: Communicate, communicate, communicate
– Big idea – shared goal/mission
– Strategy – big picture of how the pieces work together
– Tactical implementation
• Update job specs to include innovation support
• Change incentives to include innovation support
• Shower those who came before with appreciation
• Support those who try and fail and try again
Steve Blank

How to Start an Innovation Engine- 0
• Reorganize around Mission + Innovation
• Each Horizon 1 division needs a Chief Innovation Officer
• Drives Continuous Innovation
• Finds Horizon 2 opportunities
• Starts and Funds 10x the new initiatives for MVP’s
• Company needs a COO of Innovation
• Runs/funds Horizon 3 incubators with I-Corps methodology
• Runs open innovation incubators
• Provides staff and infrastructure support for Divisional Innovation
Steve Blank

How to Start an Innovation Engine- 1
• Adopt Common Language: Horizons, Lean, Pivots, MVPs, etc.
• Identify Lean Innovation Vehicles
• R&D, Engineering, Incubators, Accelerators, etc.
• Adopt Lean Product Development: Digital Services Playbook..
• Adopt Lean Metrics: Hypotheses tested, Pivots, IRL, TRL, …
• Adopt Lean Funding: TRLs & IRL
• Adopt Lean Pedagogy: Lean LaunchPad/I-Corps
• Use Lean Mgmt processes
– Agree how to “Hand-off” and “scale” small efforts (hard)
– Develop organizational processes/procedures/incentives that support
innovation (hard)
Steve Blank

Start an Innovation Engine - 2
• Educate the company on Innovation
– Communicate goals
– Communicate process (hard)
• Everyone expects detailed specs like Horizon 1 - bad
– Consolidate innovation efforts (hard)
– Recruit teams (3-4 people)
– Recruit mentors - one per team (hard)
– Get divisional cooperation (hard)
– Train the Trainers
Steve Blank

Start an Innovation Engine- 3
• Design Programs
– Emphasis on speed, urgency, evidence, pivots
– 1½ day “Train-the-Trainers”
– 6/8-week “I-Corps” programs
– Investments and adoption of H1 and H2 by divisions
• Run Programs
Steve Blank

Start an Innovation Engine - 4
• Rally around a mission not theory
• Pick something everyone agrees is a good goal
and congruent with the company’s mission
• Legitimatize the need for exploration and
exploitation
Steve Blank

Start an Innovation Engine -5
• Leadership that is capable of managing the issues
associated with multiple simultaneous Horizons
– Resource allocation
– Incentives
– Etc.
• Needs to balance a culture of risk taking, speed =
mitigation, quick to opportunities, receptive to
innovation
Steve Blank

Innovation at 50x
Steve Blank
@sgblank
www.steveblank.com
2/1/16

Innovation at 50x 031616

Innovation at 50x 031616

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