mediaX at Stanford University connects businesses with Stanford University’s world-renowned faculty to study new ways for people and technology to intersect. We are the industry affiliate program to Stanford’s H-STAR Institute. We help our members explore how the thoughtful use of technology can impact a range of fields, from entertainment to learning to commerce. Together, we’re researching innovative ways for people to collaborate, communicate, and interact with the information, products, and industries of tomorrow.

1. January
15,
2013
at S T A N F O R D U N I V E R S I T Y
Martha
G
Russell,
Execu9ve
Director
Innova9on
Ecosystems
Network

2. • Innova9on's
stakeholders
are
global.
• Form,
interface,
content
and
business
models
are
s9ll
changing.
• Future
scenarios
will
include:
– Personalized
data
with
social
intelligence
and
context
– Exponen9al
augmenta9on
of
human
capability
• Network
orchestra9on
is
a
key
management
skill.
• With
shared
vision
transforma9ons
can
be
accelerated.
at S T A N F O R D U N I V E R S I T Y

3. The REAL Issue
at S T A N F O R D U N I V E R S I T Y Deep Knowledge with Wide Applicability
IN
THE
HEART
OF
SILICON
VALLEY
IN
A
CULTURE
OF
RAPID
ITERATION,
WHERE
DISRUPTION
IS
CELEBRATED
WHERE
TALENT,
INFORMATION
AND
CAPITAL
RESOURCES
FLOURISH
THE
ISSUE
IS
NOT
THE
RATE
TECHNOLOGY
TRANSFER
THE
ISSUE
IS
THE
EFFECTIVENESS
OF
INNOVATION
AND
KNOWLEDGE
TRANSFER
WE
CALL
THIS
“COLLABORATIVE
DISCOVERY”
The
Media
X
approach
WORK
ON
BOLD
IDEAS
WITH
BUSINESS,
TEST
SUCCESS/FAILURE
CONDITIONS,
ITERATE
RESULTS
QUICKLY,
TRANSFER
INSIGHTS
AT
EVERY
STAGE

4. H-­‐STAR
HUMAN
SCIENCES
AND
TECHNOLOGIES
at S T A N F O R D U N I V E R S I T Y
ADVANCED
RESEARCH
INSTITUTE
RELATIONSHIP
INTERFACES
FOR
DISCOVERY
COLLABORATIONS
Goal:
Do
something
together
neither
of
us
could
do
by
ourselves.
Research
on
people
and
technology
—
how
people
use
technology,
how
to
be[er
design
technology
to
make
it
more
usable,
how
technology
affects
people’s
lives,
and
the
innovaEve
use
of
technologies
in
research,
educa9on,
art,
business,
commerce,
entertainment,
communica9on,
security,
and
other
walks
of
life.

5. Stanford University Medical Media !
& Information Technology !
SUMMIT Distributed Vision Lab !
a t S T A N F O R D U! I V E R S I T Y
N
DVL
Discovery Collaborations !
Electrical Engineering Psychology Span Stanford Labs!
Computer
Science EE Psy Linguistics Communication Between Humans
Philosophy Ling and Interactive Media
CS CHIMe
Phil SHL Stanford Humanities Lab
Graduate School
VHIL GSB Of Business
Virtual Human Stanford Center
Interaction Lab SCIL for Innovations
in Learning
Center for the Study Of
CSLI Language & Information
Art Digital Art
Center
EngineeringEng
& Product
Design School of Education;
Ed Education and
PBLL Law Learning Sciences
Work
Technology & Center for
Organization SSP Legal
Des Stanford Joint
PBLL Program in Design
Project Based Informatics d.school
Learning Symbolic LIFE
Laboratory Systems Program Learning in Informal and
Formal Environments

6. Stanford
spin-­‐offs
Over
2000
companies
started
by
faculty
students
and
alumni
• Abrizio
• NVIDIA
• ASK
Computer
systems
• Orbitz
• Cisco
Systems,
Inc.
• Octel
CommunicaEons
Corp.
• Dolby
Systems
• Odwalla
• eBay
• ONI
Systems
• E*Trade
• PayPal
• Electronic
Arts
• Pure
SoVware,
Inc.
• Excite,
Inc.
• Rambus,
Inc.
• Gap
• RaEonal
SoVware
• Google
• Silicon
Graphics,
Inc.
• HewleQ-­‐Packard
• Sun
Microsystems
• IDEO
• Tandem
Computers,
Inc.
• Intuit,
Inc.
• Taiwan
Semiconductor
• Learning
Company
• Tensillica
• Linked-­‐In
• Tesla
Motors
• Logitech
• Trilogy
• Mathworks
• Varian
Associates,
Inc.
• MIPS
Technologies,
Inc.
• Vmware
• Nike
• Whole
Earth
Catalog
• NeUlix
• Yahoo!
Inc.

7. Infrastructure
for
Resource
Flows
-­‐
-­‐
-­‐
Rela9onships
The Way We USED to Think About Organizations New
Organiza9onal
Chart
Based
on
Rela9onships
Relationship Capital for Co-Created Infrastructure
(Companies
are
interlocked
through
key
people
–
informaPon
flow,
norms,
mental
models.(Davis,1996)

8. Alumni
Networks

9. Silicon
Valley
Don’t
try
to
replicate
–
instead
collaborate
Geographically
concentrated,
very
ac9ve
human
network
Researchers,
business
leaders,
entrepreneurs,
funders
High
density
of
some
very
big
technology
companies
Powerful,
wealthy
university
(Stanford)
with
a
culture
of
involvement
with
industry
and
of
entrepreneurial
spinoffs
Nearby
world
class,
large
state
university
(Cal
Berkeley)
Good
local
supply
of
skilled
employees
(San
Jose
State
University)
Culture
of
risk
taking
and
acceptance
of
failure
The
world
sees
Silicon
Valley
as
a
loca9on
of
great
successes
Here
we
know
it
is
a
loca9on
of
a
great
many
“failures”
Easy
access
to
“free”
advice
and
assistance
at
the
start
Massive
amounts
of
government
funding
for
basic
research
Large
amount
of
private
funding
to
exploit
the
research
A
highly
fluid
workforce
You
can
change
employer
without
having
to
move
your
home
Anyone
can
play
Admi[ance
and
acceptance
are
based
en9rely
on
your
ideas
and
abili9es
You
are
only
as
good
as
your
latest
idea
A[rac9ve
place
to
live,
good
climate,
tolerant
and
accep9ng
culture

10. Five
Rules
for
Successful
Failure
• Iterate
quickly
– If
it
doesn’t
work,
change
something
–
ASAP
• Take
personal
responsibility
– Don’t
blame
anyone
• Share
what
you
learned
– Each
failure
includes
lessons
for
success
• Start
again
– Immediately!
• Don’t
do
it
alone
– Know,
cul9vate
and
orchestrate
your
network

11. Media
X’s
Unique
proposi9on
• Pose
a
ques9on
to
the
Stanford
thought
leaders
that
will
create
– Opportuni9es
for
discovery
collabora9ons
– On
novel
research
– That
leverages
the
latest
research
interests
– To
iden9fy
the
new
ques9ons
that
will
lead
to
– Insights
that
address
edge
ques9ons
– 3
to
5
years
out
• Par9cipate
in
the
discovery
process
to
learn
• The
best
ques9ons
and
how
to
pursue
them
• Ra9onale
of
research
pathways
–
why?
why
not?
at S T A N F O R D U N I V E R S I T Y

12. Members
Provide
the
Direc9on
• Accel
Partners
• HKUST
• ACERP
• Konica
Minolta
• Apollo
Group
• Nissan
• BT
Group
• Orange
• Cisco
• Philips
• CO3
• Sabia
Experience
• Danish
Innova9on
• Edelman
• Singularity
University
• Fu[on
• TEKES
at S T A N F O R D U N I V E R S I T Y

13. Build
Capacity
for
Insights
-­‐
Sooner
• Time
advantage
– 3
years
ahead
of
reading
the
latest
publica9ons
• Relevance
advantage
– Ques9ons
relevant
to
Konica
Minolta’s
future
• Lower
risk
of
explora9on
– Rapid
itera9on
– Know
sooner
what
works
– Externalizes
high
risk
• Capacity
building
– Iden9fy
new
exper9se
needed
– Enhance
exis9ng
exper9se
– Leverage
the
Stanford
network
at S T A N F O R D U N I V E R S I T Y

14. Analysis
of
EIT
ICT
Labs:
Trento
included
as
the
sixth
node,
more
ci9es
connected
to
coloca9on
centers,
updated
data
and
transforma9on
in
place
S9ll,
Huhtamäki,
Russell,
Rubens
(2012).
Transforming
InnovaPon
Ecosystems
Through
Network
OrchestraPon:
Case
EIT
ICT
Labs

15. Adding
San
Francisco
Bay
Area
as
“the
seventh
EIT
ICT
Labs
node”
for
contrast,
interconnec9ons,
comparison
and
benchmark
S9ll,
Huhtamäki,
Russell,
Rubens
(2012).
Transforming
InnovaPon
Ecosystems
Through
Network
OrchestraPon:
Case
EIT
ICT
Labs

16. CLICK
TO
PUBLISH
Rela?onship
Networks
Reveal
Compe?ng
Fac?ons
and
Shared
Visions
in
the
Publishing
Industry
RelaEonship
Network
analysis
can
show:
We
see:
• The
structure
and
Dynamic
innovaEon
coherence
of
compeEng
• University
parEcipaEon
facEons
• Eager
investors
• Emergence
of
shared
Many
related
sectors
visions
and
value
• Digital
media,
Saas
proposiEons
• Social
media,
mobile
• Indicators
of
industry
• eBooks
evoluEon,
signaling
Many
geographic
areas
transiEon
from
• NY,
SF,
LA,
London
‘emerging’
to
‘growth’
stage
What
this
means
is:
• RelaEonships
are
pipelines
for
talent,
informaEon
and
financial
resources.
• Value
chains
are
co-­‐
created
through
relaEonships.
SIPX,
Inc.
InnovaEon
Ecosystem
VisualizaEon
and
Analysis:
A
Study
of
the
Emerging
Publish-­‐on-­‐Demand
Industry
Martha
G
Russell,
Stanford
University;
Neil
Rubens,
University
of
Electro-­‐Communica9on;
Rahul
C.
Basole,
Georgia
Ins9tute
of
Technology;
Jukka
Huhtämaki,
Tampere
University
of
Technology,
Tim
McCormick,
Palo
Alto,
CA;
Russell
Thomas,
George
Mason
University;
Kaisa
S9ll,
VTT;
and
Jiafeng
Yu,
Shanghai,
CA

17. Personalized
Data
Will
Include
Context
and
Social
Intelligence
Exponen9al
Augmenta9on
of
Human
Poten9al
at S T A N F O R D U N I V E R S I T Y
EducaEon
-­‐
-­‐
-­‐
Business
-­‐
-­‐
-­‐
Entertainment
Context,
Content
and
Control
for
Personalized
Data
17

18. Total Engagement at Work and Play
at S T A N F O R D U N I V E R S I T Y
Gamification - Empowering Self-organizing organizations - Time to Autonomy –

19. Multi-tasking
Data – Integration - Semantics
• Personal Area Networks: New Rules, New Metrics
• Semantic and functional integration across
– TV
– Computer
– Phone
– Home
– Car
• From clouds to the edge
• Ambient and intelligent
• Personalized
• Privacy-controlled
• Fluid media
– With many IP issues and measurement challenges
at S T A N F O R D U N I V E R S I T Y
Russell, M.G. 2009 A Call for New Metrics for New Media,
http://jiad.org/article117

20. On
the
Horizon:
Transparency,
Iden9ty
&
Persuasion

21. Semantic Integration Technologies
• Sensors
• Mobile devices
On the Horizon: The Intelligent Coach for Health and Well-being

23. Digital Footprints
When People Become the Content of Media
Interact with Your Digital Self
Infinite Reality Emotional Interfaces Social Affordances

24. Quantified Self
On the Horizon: The Quantified Self

25. Skill
of
the
Future
=
Network
Orchestra9on
25

26. Shared Vision Transforms
Iterative
Impact Alignment
Co-Create
Value
Shared
Vision
Transforma9on
Event
Coalition
Interact &
Feedback
Martha G. Russell, Kaisa Still, Jukka Huhtamaki, and Neil Rubens, “Transforming innovation ecosystems through shared vision
and network orchestration,” Triple Helix IX Conference, Stanford University, July 13, 2011.

27. What Can We Do Together
That Neither of Us Could Do Alone?
at S T A N F O R D U N I V E R S I T Y
Thank You
Martha.Russell@stanford.edu
www.innovation-ecosystems.org
http://mediax.stanford.edu
• Innovation Ecosystems Require Network Orchestration
– Know
– Cultivate
– Orchestrate