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Innovation at 50x
Steve Blank
@sgblank
www.steveblank.com
03/16/16
What is Innovation?
Innovation ≠ Incubator
Innovation ≠ Accelerator
Innovation ≠ Startup
Innovation ≠ Lean Anything
Innovation ≠ Open
Innovation ≠ Reorganization
Innovation ≠ Incubator
Innovation ≠ Accelerator
Innovation ≠ Startup
Innovation ≠ Café’s
These are all physical
places to do innovation
Innovation ≠ Incubator
Innovation ≠ Accelerator
Innovation ≠ Startup
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
Continuous Innovation
Steve Blank
what’s this mean?
∧
20th Century Corporate Lifecycle
21st Century Corporate Lifecycle
Continuous disruption requires
Continuous Innovation
Steve Blank
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
Source: James March, Charles O’Reilly, Michael Tushman
An Ambidextrous organization
achieves breakthrough innovations
while relentlessly improving the
way they execute current business
model
Source: James March, Charles O’Reilly, Michael Tushman
An Ambidextrous organization
achieves breakthrough innovations
while relentlessly improving the way
they execute current business model
and serve existing customers
Source: James March, Charles O’Reilly, Michael Tushman
Here’s How
Types of
Company Innovation
Steve Blank
Three Horizons of Innovation
Source: Baghai, Coley, White
Mature Business
our established capabilities
Rapidly Growing Business Emerging Business
Three Horizons of Innovation
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
Three Horizons of Innovation
Existing Business Model:
Process Innovation
Execute Core Mission
Known
Three Horizons of Innovation
Existing Business Model:
Process Innovation
Execute
Known
Partially Known
New Opportunities via
Business Model Innovation
Extends Core Business
Three Horizons of Innovation
Existing Business Model:
Process Innovation
Execute
New Opportunities via
Business Model Innovation
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
The Lean Methodology
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
Source: Alexander Osterwalder- Business Model Generation
1. Frame Hypotheses
• Frame Hypotheses 
1. Frame Hypotheses
• Frame Hypotheses Business Model Canvas
Business Model Canvas
Source: Alexander Osterwalder- Business Model Generation
2. Test Hypotheses
• Frame Hypotheses
• Test Hypotheses
Business Model
Customer Development


Customer Development is how you search for the model
Customer Development
Turning the Business Model Canvas Into Facts
9 Guesses
Guess Guess
Guess
Guess
Guess
Guess
Guess
GuessGuess
Customers
Channel
Customer
Relationships
Revenue Model
Source: Alexander Osterwalder- Business Model Generation
Customer Development is
Hypothesis Testing
3. Build Incrementally & Iteratively
• Frame Hypotheses
• Test Hypotheses
• Build the product
incrementally &
Iteratively
Business Model
Customer Development
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
Customer Development
2003
Blank
Agile Engineering
2011
Ries
Business Model Canvas
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
How Does This Really Work?
Example 1:
Stanford Team
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
Management Consulting
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
Management Consulting
Scott Steinberg,
MBA
Marketing Growth Strategy
Management Consulting
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?
What are current online
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
✘
What about the consumer?
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
What we thought: Consumer VP
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
• Ability to follow up with
consumer
- Faster turnaround
• Give additional context in
traditional surveys
• Data API providers
• Data aggregators
• Marketing agencies
• Panel participants
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
• Provide sense of
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?
What are current online
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
3. Custom research studies
4. Linking data to client databases
Pricing based on sample size/type, data type/amount, number of questions,
feedback time
Key Resources
Key ActivitiesKey Partners Value Proposition Customer
Segments
Customer
Relationships
Channels
Resulting Business Canvas
Consumers
• Smartphone using
consumers who shop online
• Millennials
• Existing research
participants
• People who currently give to
charity
Enterprises
• Retail (traditional)
• Retail (e-commerce)
• CPG with online sales
• 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
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
• Easy and fast way to do it
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
• Data API providers
• Data aggregators
• Marketing agencies
• Panel participants
• 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
• Existing research
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
3. Custom research studies
4. Linking data to client databases
Pricing based on sample size/type, data type/amount, number of questions,
feedback time
Key Resources
Key ActivitiesKey Partners Value Proposition Customer
Segments
Customer
Relationships
Channels
Consumers
• Online shoppers
• Current charity givers
• Millennials
• Existing research
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
• Easy and fast way to do it
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
• Data API providers
• Data aggregators
• 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
Appendix
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:
How do surveys work?
2 Market research team writes a survey that will inform the answer
Demographics
● Age?
● Gender?
● ...
Behavior
● Where did you buy?
● What? How much?
● ...
Emotions / Feelings
● Why did you buy?
● What matters to
you?
Survey
5 - 10 minutes of
questions
10 - 15 minutes
of questions
A quick primer:
How do surveys work?
3 Survey sent to consumers through a ‘panel provider’
Demographics
● Age?
● Gender?
● ...
Behavior
● Where did you buy?
● What? How much?
● ...
Emotions / Feelings
● Why did you buy?
● What matters to you?
● ...
Survey
$ / person
Panel ProviderMarket Research team
Demographics
● Age?
● Gender?
● ...
Behavior
● Where did you buy?
● What? How much?
● ...
Emotions / Feelings
● Why did you buy?
● What matters to you?
● ...
Survey
A quick primer:
How do surveys work?
4 Consumers answer survey based on their memory
Panel ProviderMarket Research team
Self
reported
data
A quick primer:
How do surveys work?
5 Market research team analyzes data to develop an answer
Market Research team
Insight &
recommended
business action
Demographics
● Age?
● Gender?
● ...
Behavior
● Where did you buy?
● What? How much?
● ...
Emotions / Feelings
● Why did you buy?
● What matters to you?
● ...
Survey
...Where we thought we fit in
4 Consumers answer survey based on their memory
Panel ProviderMarket Research team
3 Survey sent to consumers through a ‘panel provider’
Why can’t this be based on actual
(vs. self reported) data?
Demographics
● Age?
● Gender?
● ...
Behavior
● Where did you buy?
● What? How much?
● ...
Emotions / Feelings
● Why did you buy?
● What matters to you?
● ...
Survey
...Where we thought we fit in
4 Consumers answer survey based on their memory
Panel ProviderMarket Research team
3 Survey sent to consumers through a ‘panel provider’
...let’s be a “next gen” panel
provider that merges real data
with opinions
...Where we thought we fit in
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
Other learnings
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
ŠTechnology 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
Version 2 - Expanded Team 198
Customer Discovery
Team 198
LOWES
BLAINE Window Repair Thompson Creek Windows
Banner Glass Inc.
Version 3 - Expanded Team 198
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
Version 4 - Expanded Team 198
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
Version 5 - Expanded Team 198
Advanced Energy Conference
Team 198
Jacobs Javits Center Exterior Curtain Wall
Advanced Energy Conference 2013 - NYC
Version 6 - Expanded Team 198
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)
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
ŠTechnology 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
Existing Business Model:
Process Innovation
Execute
New/Disruptive
Business Model
Search
New Opportunities via
Business Model Innovation
Execute/Search
Known
Unknown
Partially known
Lean Innovation Mgmt
Process
Mgmt
Managing Three Horizons of
Innovation - Goal
Existing Business Model:
Continuous Innovation
Execute
New/Disruptive
Business Model
Search
New Opportunities via
Business Model Innovation
Execute/Search
Known
Unknown
Partially known
Lean Innovation Mgmt
Innovation Metrics
NASA
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
NASA/DOD Technology Readiness
Levels 5 & 6
Demo Prototype
• Breadboard validation outside the building
• System demo in real-world
Research
Concept
Demo
NASA/DOD Technology Readiness
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
Investment Readiness Level
We can do the same
for new ventures
Emphasis is on data
Investment Readiness Level
• 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
Investment Readiness:
Levels 3 & 4
Problem / Solution Fit
• Problem Solution fit
• Low fidelity MVP
Hypotheses
Problem/Solution
Investment Readiness:
Levels 5 & 6
Validate
• Product/Market fit
• Right side of canvas
Hypotheses
Problem/Solution
Product/Market fit
Investment Readiness:
Levels 7 & 8
Validate
• Left side of canvas
Hypotheses
Problem/Solution
Product/Market fit
Investment Readiness:
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
Horizon 3 Project
Horizon 1 Management
Horizon 1 Management
Horizon 1 Management
The Problem
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
Company Incentives & Goals
In support of Innovation in All 3 Horizons
Disruptive
Innovation
Steve Blank
• Company operates on goals and incentives
• Incent mavericks, incent support, incent adoption
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
Company Incentives & Goals
In support of Innovation in All 3 Horizons
Disruptive
Innovation
Steve Blank
• Company operates on goals and incentives
• Incent mavericks, incent support, incent adoption
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
Why Innovation Fails
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
Evangelos Simoudis/Steve Blank
Horizon 1
The Limits of Current Horizons
189
Develop-
ment
Research
Evangelos Simoudis/Steve Blank
Horizon 1
Develop-
ment
Research
Business
Units
Horizon 1
The Limits of Current Horizons
Evangelos Simoudis/Steve Blank
Extend the
Business Model
The Limits of Current Horizons
Evangelos Simoudis/Steve Blank
Horizon 2
The Limits of Current Horizons
Develop-
ment
Research
Business
Units
Customers
Customers
Customers
Evangelos Simoudis/Steve Blank
Horizon 2
The Limits of Current Horizons
Develop-
ment
Research
Business
Units
Customers
Customers
Customers
Evangelos Simoudis/Steve Blank
• 90% of R&D dollars support existing products
• Research = adv development to support existing products
Horizon 1 & 2
Unknown
Business Model
The Limits of Current Horizons
Evangelos Simoudis/Steve Blank
Horizon 3
The Limits of Current Horizons
Develop-
ment
Research
Business
Units
Customers
Customers
Customers
Evangelos Simoudis/Steve Blank
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
Evangelos Simoudis/Steve Blank
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
Steve Blank/Evangelous Simoudis
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
Steve Blank/Evangelous Simoudis
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
Steve Blank/Evangelous Simoudis
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
Evangelos Simoudis/Steve Blank
New
Unit
New
Unit Existing
BU
H1 Corporation
Existing
BU
2) augmenting the H1 corporation
through their presence.
Outposts Change the Culture
Startups
Evangelos Simoudis/Steve Blank
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
Thanks!
sblank@kandsranch.com
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
Thanks!
sblank@kandsranch.com
Innovation at 50x
Steve Blank
@sgblank
www.steveblank.com
2/1/16

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Innovation at 50x 031616

  • 1. Innovation at 50x Steve Blank @sgblank www.steveblank.com 03/16/16
  • 3. Innovation ≠ Incubator Innovation ≠ Accelerator Innovation ≠ Startup Innovation ≠ Lean Anything Innovation ≠ Open Innovation ≠ Reorganization
  • 4. Innovation ≠ Incubator Innovation ≠ Accelerator Innovation ≠ Startup Innovation ≠ Café’s These are all physical places to do innovation
  • 5. Innovation ≠ Incubator Innovation ≠ Accelerator Innovation ≠ Startup Innovation ≠ Café’s These are all physical places to do innovation Having them does not guarantee any innovation will happen
  • 6. 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, StateGateÂŽ, ECV, Pivots, IRL, TRL, … • Funding – VC, Corporate VC, M&A, etc.
  • 7. 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, StateGateÂŽ, ECV, Pivots, IRL, TRL,… • Funding – VC, Corporate VC, M&A, Incremental, etc.
  • 8. Innovation Is? Satisfying users current or future wants/needs by turning an idea into a product or service
  • 9. 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
  • 10. 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”)
  • 12. Continuous disruption requires Continuous Innovation Steve Blank what’s this mean? ∧
  • 16. Continuous Innovation requires new management tools Steve Blank
  • 17. Continuous Innovation requires new management tools Lean Innovation Management Steve Blank
  • 18. Why Lean Innovation Management? 10x the number of initiatives in 1/5 the amount of time 50x
  • 19. Can You Create an Organization that Executes and Innovates?
  • 20. Can You Create an Organization that Executes and Innovates? It’s Called an Ambidextrous Organization Source: James March, Charles O’Reilly, Michael Tushman
  • 21. An Ambidextrous organization achieves breakthrough innovations Source: James March, Charles O’Reilly, Michael Tushman
  • 22. An Ambidextrous organization achieves breakthrough innovations while relentlessly improving the way they execute current business model Source: James March, Charles O’Reilly, Michael Tushman
  • 23. An Ambidextrous organization achieves breakthrough innovations while relentlessly improving the way they execute current business model and serve existing customers Source: James March, Charles O’Reilly, Michael Tushman
  • 26. Three Horizons of Innovation Source: Baghai, Coley, White Mature Business our established capabilities Rapidly Growing Business Emerging Business
  • 27. Three Horizons of Innovation Source: modified Baghai, Coley, White our established capabilities
  • 28. 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
  • 29. Three Horizons of Innovation Existing Business Model: Process Innovation Execute Core Mission Known
  • 30. Three Horizons of Innovation Existing Business Model: Process Innovation Execute Known Partially Known New Opportunities via Business Model Innovation Extends Core Business
  • 31. Three Horizons of Innovation Existing Business Model: Process Innovation Execute New Opportunities via Business Model Innovation Execute/Search Known Unknown Partially known New/Disruptive Business Model Explores
  • 32. Capabilities/Risk Assessment Existing Capabilities Low Risk Need New Capabilities High Risk Some Capabilities Moderate Risk Known Unknown Partially known
  • 33. Innovation Allocation Across the Horizons Known Unknown Partially known 60-70% 20-30% 5-10%
  • 34. 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
  • 35. 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
  • 36. 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
  • 37. 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
  • 38. 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
  • 39. Lean Innovation Delivers Products and Services that users want and need in a fraction of the time
  • 41. 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
  • 42. 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 Source: Alexander Osterwalder- Business Model Generation
  • 43. 1. Frame Hypotheses • Frame Hypotheses 
  • 44. 1. Frame Hypotheses • Frame Hypotheses Business Model Canvas
  • 45. Business Model Canvas Source: Alexander Osterwalder- Business Model Generation
  • 46. 2. Test Hypotheses • Frame Hypotheses • Test Hypotheses Business Model Customer Development   Customer Development is how you search for the model
  • 47. Customer Development Turning the Business Model Canvas Into Facts
  • 50. 3. Build Incrementally & Iteratively • Frame Hypotheses • Test Hypotheses • Build the product incrementally & Iteratively Business Model Customer Development Agile Engineering   
  • 51. 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…
  • 52. 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
  • 53. 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
  • 54. Part 1 Agile Engineering + Part 2 Part 3 Elements of Lean Startup
  • 55. Lean Gets Theory Customer Development 2003 Blank Agile Engineering 2011 Ries Business Model Canvas 2010 Osterwalder HBR Cover 2013
  • 56. 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
  • 57. How Does This Really Work?
  • 59. 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 Management Consulting Karan Singhal, Undergrad CS Web Development User Interface Design Share&Tell
  • 60. Share&Tell Yegor Tkachenko, MS Marketing Analytics Machine Learning Eric Peter, CS & MBA Consumer Insight Expert Management Consulting Scott Steinberg, MBA Marketing Growth Strategy Management Consulting 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
  • 61. 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
  • 62. 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
  • 63. 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
  • 64. 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
  • 65. 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
  • 66. 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
  • 67. 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 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 ✘
  • 68. What about the consumer?
  • 69. 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 What we thought: Consumer VP 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 • Ability to follow up with consumer - Faster turnaround • Give additional context in traditional surveys • Data API providers • Data aggregators • Marketing agencies • Panel participants 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
  • 70. 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
  • 71. Experiment: Take an MVP on an iPad to the mall Consumer Week 1-3
  • 72. 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
  • 73. 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
  • 74. 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
  • 75. Value Proposition Consumer: • 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 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
  • 76. Let’s first focus on narrowing down enterprise value prop to see what data we need.
  • 77. 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? What are current online shopping trends? ✘ ✘ Enterprise Week 4 14 more enterprise interviews to (in)validate our hypothesized value props and identify the most acute needs
  • 78. “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
  • 79. Well, why not focus on data that’s easiest to get? Most Sensitive Least Sensitive Google Survey Consumer Week 5
  • 80. And heard from companies that Amazon data is big pain point Enterprise Week 5
  • 81. 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
  • 82. 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 3. Custom research studies 4. Linking data to client databases Pricing based on sample size/type, data type/amount, number of questions, feedback time Key Resources Key ActivitiesKey Partners Value Proposition Customer Segments Customer Relationships Channels Resulting Business Canvas Consumers • Smartphone using consumers who shop online • Millennials • Existing research participants • People who currently give to charity Enterprises • Retail (traditional) • Retail (e-commerce) • CPG with online sales • 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 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 • Easy and fast way to do it 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 • Data API providers • Data aggregators • Marketing agencies • Panel participants • 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
  • 83. As a result: Develop low-fi MVP Enterprise Week 5-6
  • 84. Now, how do we incentivize consumers to provide Amazon data? Consumer Week 5
  • 85. 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
  • 86. What we did: 10+ Customer Discovery interviews...and 2,000+ survey responses Consumer Week 5
  • 87. 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
  • 88. 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
  • 89. As a result: 3-sided market Consumer Week 6
  • 90. 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 • Existing research participants Segment Consumer: • Millennials • People who donate to charity Segment Consumer Week 6 ✘ ✘
  • 91. 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
  • 92. 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 ✘
  • 93. 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
  • 94. 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.
  • 95. What we did: Tested ‘direct to consumer’ using a high fidelity MVP... https://www.datadoesgood.com Consumer Week 7-9
  • 96. 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
  • 97. 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 3. Custom research studies 4. Linking data to client databases Pricing based on sample size/type, data type/amount, number of questions, feedback time Key Resources Key ActivitiesKey Partners Value Proposition Customer Segments Customer Relationships Channels Consumers • Online shoppers • Current charity givers • Millennials • Existing research 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 • Easy and fast way to do it 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 • Data API providers • Data aggregators • E-commerce retailers • Ad networks and programmatic ad buyers? Final Business Model Canvas Week 10
  • 98. 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
  • 100. 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
  • 101. ...for 3 generic enterprise segments Enterprise Week 4 Retailers Traditional E-Commerce 1 2 CPG With online sales Without online sales 3
  • 102. 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
  • 103. 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?
  • 104. A quick primer: How do surveys work? 2 Market research team writes a survey that will inform the answer Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? Survey 5 - 10 minutes of questions 10 - 15 minutes of questions
  • 105. A quick primer: How do surveys work? 3 Survey sent to consumers through a ‘panel provider’ Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey $ / person Panel ProviderMarket Research team
  • 106. Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey A quick primer: How do surveys work? 4 Consumers answer survey based on their memory Panel ProviderMarket Research team Self reported data
  • 107. A quick primer: How do surveys work? 5 Market research team analyzes data to develop an answer Market Research team Insight & recommended business action
  • 108. Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey ...Where we thought we fit in 4 Consumers answer survey based on their memory Panel ProviderMarket Research team 3 Survey sent to consumers through a ‘panel provider’ Why can’t this be based on actual (vs. self reported) data?
  • 109. Demographics ● Age? ● Gender? ● ... Behavior ● Where did you buy? ● What? How much? ● ... Emotions / Feelings ● Why did you buy? ● What matters to you? ● ... Survey ...Where we thought we fit in 4 Consumers answer survey based on their memory Panel ProviderMarket Research team 3 Survey sent to consumers through a ‘panel provider’ ...let’s be a “next gen” panel provider that merges real data with opinions
  • 110. ...Where we thought we fit in 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
  • 112. 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
  • 113. 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
  • 114. 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
  • 115. Example 2: National Science Foundation Team
  • 116. Team 198 ŠTechnology 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
  • 117. 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
  • 118. 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
  • 119. 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
  • 120. 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
  • 121. 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
  • 122. Version 2 - Expanded Team 198
  • 123. Customer Discovery Team 198 LOWES BLAINE Window Repair Thompson Creek Windows Banner Glass Inc.
  • 124. Version 3 - Expanded Team 198
  • 125. 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
  • 126. 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
  • 127. Version 4 - Expanded Team 198
  • 128. 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
  • 129. Version 5 - Expanded Team 198
  • 130. Advanced Energy Conference Team 198 Jacobs Javits Center Exterior Curtain Wall Advanced Energy Conference 2013 - NYC
  • 131. Version 6 - Expanded Team 198
  • 132. 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)
  • 133. 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)
  • 134. 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
  • 135. Competitive Threats • Manufacturers of Low-E • “Flip-of-a-switch” (electrochromics) • Metallic Low-E Plus • Transitions (photochromics) • Lowering Energy Costs Team 198 electrochromics
  • 136. 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
  • 137. Team 198 ŠTechnology Review GO Tech Video Lessons Learned Video http://youtu.be/RIR2SiQd1pk http://youtu.be/8q8l5i3ISeU
  • 138. 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
  • 139. Managing Three Horizons of Innovation - Current Existing Business Model: Process Innovation Execute New/Disruptive Business Model Search New Opportunities via Business Model Innovation Execute/Search Known Unknown Partially known Lean Innovation Mgmt Process Mgmt
  • 140. Managing Three Horizons of Innovation - Goal Existing Business Model: Continuous Innovation Execute New/Disruptive Business Model Search New Opportunities via Business Model Innovation Execute/Search Known Unknown Partially known Lean Innovation Mgmt
  • 142. NASA
  • 143. NASA/DOD Technology Readiness Level (TRL) • Formal Way to assess project maturity • Quantify Relative Risks • Data Driven • Adopted by NASA, DOD, FAA, ESA…
  • 144. NASA/DOD Technology Readiness: Levels 1 & 2 Basic Technology Research • Basic principles observed • Technology concept formulated Concept
  • 145. NASA/DOD Technology Readiness Levels 3 & 4 Research to prove Feasibility • Experimental proof of concept • Breadboard validation in lab Research Concept
  • 146. NASA/DOD Technology Readiness Levels 5 & 6 Demo Prototype • Breadboard validation outside the building • System demo in real-world Research Concept Demo
  • 147. NASA/DOD Technology Readiness Levels 7, 8, 9 Deployment • System Development • System deployed in real-world Research Concept Demo
  • 148. What Can We Do With Customer Discovery Data? The Investment Readiness Level
  • 149. Investment Readiness Level We can do the same for new ventures
  • 150. Investment Readiness Level We can do the same for new ventures Emphasis is on data
  • 151. Investment Readiness Level • 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
  • 152. Investment Readiness: Levels 1 & 2 Hypotheses • Value Proposition summarized • Canvas hypotheses articulated Hypotheses
  • 153. Investment Readiness: Levels 3 & 4 Problem / Solution Fit • Problem Solution fit • Low fidelity MVP Hypotheses Problem/Solution
  • 154. Investment Readiness: Levels 5 & 6 Validate • Product/Market fit • Right side of canvas Hypotheses Problem/Solution Product/Market fit
  • 155. Investment Readiness: Levels 7 & 8 Validate • Left side of canvas Hypotheses Problem/Solution Product/Market fit
  • 156. Investment Readiness: Levels 9 Metrics That Matter Hypotheses Problem/Solution Product/Market fit Left side of the canvas
  • 157. 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
  • 158. Horizon 1 Procedures Meets a Horizon 3 Project Steve Blank
  • 164. 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
  • 165. 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
  • 166. Success Creates “Debt” Success creates • Technical debt • Organizational debt • Refactoring “cleans up” debt by restructuring it Refactoring Steve Blank New/Disruptive Innovation
  • 167. 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
  • 168. 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
  • 169. 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
  • 170. “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
  • 171. 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
  • 172. Company Incentives & Goals In support of Innovation in All 3 Horizons Disruptive Innovation Steve Blank • Company operates on goals and incentives • Incent mavericks, incent support, incent adoption 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
  • 173. Company Incentives & Goals In support of Innovation in All 3 Horizons Disruptive Innovation Steve Blank • Company operates on goals and incentives • Incent mavericks, incent support, incent adoption 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
  • 174. 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
  • 175. 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
  • 176. 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
  • 178. 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”
  • 179. 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
  • 180. Innovation Is a Buzzword • Stop using it to describe everything Solution: • Use the Horizon 1, 2 & 3 metaphor
  • 181. 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
  • 182. 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
  • 183. 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
  • 184. Sales Freezes Talking to Customers • Sales says “no one can talk to our customers” Solution: • Customer Discovery is not pitching new products Steve Blank
  • 185. 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
  • 187. Towards New Horizons Rethinking the Enterprise take best practices from startups and apply it to the corporation
  • 188. Hor Known Business Model The Limits of Current Horizons Evangelos Simoudis/Steve Blank Horizon 1
  • 189. The Limits of Current Horizons 189 Develop- ment Research Evangelos Simoudis/Steve Blank Horizon 1
  • 190. Develop- ment Research Business Units Horizon 1 The Limits of Current Horizons Evangelos Simoudis/Steve Blank
  • 191. Extend the Business Model The Limits of Current Horizons Evangelos Simoudis/Steve Blank Horizon 2
  • 192. The Limits of Current Horizons Develop- ment Research Business Units Customers Customers Customers Evangelos Simoudis/Steve Blank Horizon 2
  • 193. The Limits of Current Horizons Develop- ment Research Business Units Customers Customers Customers Evangelos Simoudis/Steve Blank • 90% of R&D dollars support existing products • Research = adv development to support existing products Horizon 1 & 2
  • 194. Unknown Business Model The Limits of Current Horizons Evangelos Simoudis/Steve Blank Horizon 3
  • 195. The Limits of Current Horizons Develop- ment Research Business Units Customers Customers Customers Evangelos Simoudis/Steve Blank Horizon 3
  • 196. 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
  • 198. 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
  • 199. 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 Steve Blank/Evangelous Simoudis Innovation Outpost Business model & Technology Innovations Spin ins New Business Unit Startups Startups Startups
  • 200. 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 Steve Blank/Evangelous Simoudis 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
  • 201. 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 Steve Blank/Evangelous Simoudis 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
  • 202. 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 Evangelos Simoudis/Steve Blank
  • 203. New Unit New Unit Existing BU H1 Corporation Existing BU 2) augmenting the H1 corporation through their presence. Outposts Change the Culture Startups Evangelos Simoudis/Steve Blank
  • 204. 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
  • 206. 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
  • 207. 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
  • 208. 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
  • 209. 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
  • 210. 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
  • 211. 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
  • 212. 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
  • 214. Innovation at 50x Steve Blank @sgblank www.steveblank.com 2/1/16