Service innovation
The Information and Service Economy
October 29 2007
Bob Glushko and Anno Saxenian
Classic linear model of innovation
 Powerful, simple conceptualization;
useful but not the whole story
 Science base=> basic research=>
applied research=> invention=>
prototype=> development=>
commercialization=> diffusion=>
technical progress=> econ growth
Example of new drug
 Basic research: microbiology
 Applied research: screening
compounds, testing on animals
 Invention: lab success
 Development: clinical trials
 Commercialization: package, market
 Diffusion: spreads to doctors and
patient populations
Linear model of innovation
 Science base=> basic research=> applied
research=> invention=> prototype=>
development=> commercialization=>
diffusion=> technical progress=> econ
growth
 Which segments are “innovation”?
 What purposes served by this model?
 How exogenous is science?
Limits of linear model
 Feedback loops & backward linkages
 Applied research/innovation=> science
 Commercialization=> new innovation
 Invention/innovation=> science base via
improvements in instrumentation
 “Learning by doing” in manufacturing
 Chemicals, airframes, semiconductors
 “Learning by using” user feedback
 Software, skateboards
Uncertainty and chance
 Many examples in history of technology of
innovations under-appreciated at the time
 Laser, radio, computer
 Laser (Light Amplification by Stimulated
Emission of Radiation)
 Invented at Bell Labs circa 1960
 Lawyers didn’t apply for patents, not useful
 Now used in fiber-optic cables as well as
navigation, CDs, surgery, navigation etc.
Linear model and organization
 Linear model => Closed industrial
model of innovation: Focused internal
R&D, clear firm boundaries, IP rights,
virtuous cycles of reinvestment
 Examples: AT&T Bell Labs, Xerox
PARC
Open innovation
 Open innovation: combine external
and internal R&D into architectures
and systems whose requirements are
defined by a business model; blurs
boundaries of firm R&D
 Examples: Silicon Valley, Hollywood,
P&G
Closed v. open innovation
 All smart people in the
field work for us
 To profit from R&D
must discover, develop
& ship
 We can get to market
first if we innovate
 First company to
market will win
 If we create most and
best ideas, we’ll win
 We must control our IP
 There are smart people
outside & inside
 External R&D can add
value alongside internal
 We need not originate
research to benefit
 Building better business
model more important
than first to market
 We win if we make best
use internal & external
 We can profit from
others’ use of our IP
and benefit from theirs
when appropriate
Democratizing innovation
 User-centered innovation offers advantages over
traditional producer-centered innovation, which
concentrates innovation support resources on
just a few pre-selected potential innovators
 Users can develop what they want, enhances
motivation
 Users need not develop everything they need;
they can benefit from innovations developed and
freely shared with others
User and producer-centered
 Economies of scale v. economies of scope
(heterogeneous info & resources among users)
 Producers integrate themselves into usercentric innovation model
 Provide custom production or “foundry”
services to users: faster, better, cheaper;
 Produce user-developed innovations
commercially;
 Sell product-development platforms or sell
other complementary products
 For information products, no manufacturer is
required & general distribution occurs mainly
through communities
Democratization of design
 Why now?
 Increasingly capable & cheaper tools that
require less skill and training to use
 Tools for communication make it easier for
user-innovators to gain access to rich libraries
of modifiable innovations and components that
have been placed in the public domain
 Today users design sophisticated new products,
services, music and art
 Open source software movement as key example
 Web 2.0 explicitly recognizes users add value
Service innovation: new markets
 Market-creating service innovations
v. incrementally improved services
 Examples: Cirque du Soleil, University of
Phoenix
 Service v. product innovation
1. Service providers part of innovation
2. Local delivery capacity required for inperson services
3. No physical product to brand
Market-creating service innovations
1. Flexible solutions
 FedEx
 eBay
 CNN
2. Controllable convenience
 Google
 Netflix
 Skype
Market-creating service innovations
3. Comfortable gains
 Starbucks
 Cirque du Soleil
 Barnes & Noble
4. Respectful access
 Ball Memorial Hospital
 Southwest Airlines
 Hertz #1 Club Gold
Typology of service innovation
1. Business model innovation:
Substantial change how revenues and profits
earned (business model); often accompanied by
organizational changes
2. Process/system innovation:
Changes in how information exchanged between
customer and service provider, bus processes
3. Service product innovation:
Introduction of entirely new services
In reality all 3 are interrelated; an iterative
process
Creation networks
 “Networks of creation:” hundreds or thousands
of participants from diverse institutions
collaborate to create new knowledge, learn
from one another, and appropriate and build
on one another’s work—under guidance of a
network organizer.
 Rather than protecting and hoarding
knowledge, offer to others to gain access to
broader knowledge flows.
 Opportunity to jointly create new knowledge
and deliver innovations to market by
collaborating closely; long-term, interactive
relationships with networks of suppliers,
customers, specialists, even amateurs
Coordination challenges
Three primary challenges in creation process:
1. Access and develop highly distributed talent
2. Provide appropriate contexts for participants
to come together, collaborate to experiment,
tinker, and innovate (least actively managed)
3. Effectively integrate the creations of diverse
participants into shared releases (most
actively managed)
Central importance of performance
requirements and feedback loops to insure
continuous improvement
Product development
An iterative problem-solving (trial and error) process
DESIGN
BUILD
RUN
ANALYZE
Product development in new era
1.
2.
3.
Rapid movement from concept to prototype (rapid
prototyping)
Define early and frequent rounds of performance
tests to learn quickly and adapt designs
Establish broad-based communications mechanisms
to share performance data
“Managers must move their focus beyond narrow
efficiency gains …and embrace the possibilities that
uncertainty creates.” J.S. Brown & J. Hagel (2006)
What is Web 2.0? (Tim O’Reilly)
 Strategic positioning
 The web as a platform (Google v. Netscape)
 User positioning
 You control your own data (Data is the next Intel
Inside)
 Core competencies
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Services, not packaged software
Architecture of participation (RSS)
Cost-effective scalability
Re-mixable data source and transformations
Software above level of single device (iPod/iTunes)
Collective intelligence (hyperlinks, users as co
developers)