Innovation
Dynamics:
Industry & Technology Roadmapping
IAP 2003 ~ 1/21/03
Joost Bonsen
jpbonsen@alum.mit.edu
http://web.media.mit.edu/~jpbonsen/
Technology Roadmapping
(TRM)
•
•
•
•
•
•
•
•
Tech-Industry-level of observation. & analysis
Broad faculty participation, Multi-Disciplinary
Covering the Emerging Technology spectrum
Viewing Business Implications & Context of
Technology trends
Unifying, Big-Picture perspective
Long-term view, “futurecasting”
Neutral-ground for discussion among industry
players & MIT research sponsors
Appealing to MBA, MEng, & industrially-inclined PhD
students through 15.795 TRM Research Seminar
Technology
Roadmapping
Fall Semester 2002 Class
Offering
Emerging MIT Sloan research
theme
Generalizing & Enriching Historic
Technology & Demand Trends
• Historical Efforts
–
–
–
–
Moore’s Law
Electronic Devices
Sematech Roadmap
Disk Drives
• Ongoing
– Optical Networking
– Wireless
• Future
– New technologies
…
Transistors per chip
Moore’s Law
109
?
108
Pentium 80786
Pro
107
80486
Pentium
106
80386
80286
105
8086
8080
104
4004
103
1970
1975
1980
1985
1990
1995
2000
2005
2010
Year
Source: Joel Birnbaum, HP, Lecture at APS Centennial, Atlanta, 1999
Source: Fine, MIT
Roadmap for Electronic Devices
Number of chip components
295oK
1018
Classical Age
Quantum Age
1016
77oK
1014
4oK
2010
SIA Roadmap 2005
Quantum State Switch
2000
1995
1012
1010
108 Historical Trend
1990
6
10
1980
104
CMOS
1970
102
101
100
10-1
Feature size (microns)
Horst D. Simon
10-2
10-3
Source: Fine, MIT
International Technology Roadmap
for Semiconductors ‘99
Year
2005
2008
2011
2014
Technology (nm)
100
70
50
35
DRAM chip area (mm2)
526
603
691
792
DRAM capacity (Gb)
8
64
MPU chip area (mm2)
622
713
817
937
MPU transistors (x109)
0.9
2.5
7.0
20.0
MPU Clock Rate (GHz)
3.5
6.0
10.0
13.5
Source: Fine, MIT
Disk Drive Development
1978-1991
Disk Drive Dominant
Generation Producer
14”
8”
IBM
Dominant
Usage
Approx cost per
Megabyte
mainframe
$750
Quantum Mini-computer
$100
5.25”
Seagate
Desktop PC
$30
3.5”
Conner
Portable PC
$7
2.5”
Conner
Notebook PC
$2
From 1991-98, Disk Drive storage density increased by 60%/year
while semiconductor density grew ~50%/year. Disk Drive cost
per megabyte in 1997 was ~ $ .10
Source: Fine, MIT
Optical Networking
Voice growth
Capacity
OC768
OC192
OC48
OC12
TDM line rate
growth
Data growth
Optical network
capacity growth
Time
Source: Fine, MIT
Optical Technology Evolution:
Navigating the Generations
with an Immature Technology
1
2
3
4
5
Timeline
Now
Starting
Starting
3-5 years
5-15 years
Stage
Discrete
Components
Hybrid
Integration
Low-level
monolithic
integration
Medium
Monolithic
integration
High-level
monolithic
integration
Examples
MUX/
DEMUX
TX/RX module
OADM
TX/RX
module
OADM
OADM,
Transponder
Switch Matrix
Transponder
Core
Technologies
FBGs,
film,
fused
mirrors
Silicon
Bench,
Ceramic
substrates
Silica
Silicon
InP
InP, ??
InP, ??
How many
Functions?
1
2-5
2-5
5-10
10-XXX
Industry
Structure
Integrated
Integrated/
Horizontal
Integrated/
Thinfiber,
Horizontal
Dr. Yanming Liu, MIT & Corning
DOUBLE
HELIX
DOUBLE
HELIX
Source: Fine, MIT
Supply Chain Volatility Amplification:
“The Bullwhip Effect”
Customer
Retailer
Distributor
Information lags
Delivery lags
Over- and underordering
Misperceptions of feedback
Lumpiness in ordering
Chain accumulations
Factory
Tier 1 Supplier Equipment
SOLUTIONS:
Countercyclical Markets
Countercyclical Technologies
Collaborative channel mgmt.
(Cincinnati Milacron & Boeing)
Source: Fine, MIT
Supply Chain Volatility Amplification:
Machine Tools at the tip of the Bullwhip
% Chg. GDP
% Chg. Vehicle Production Index
% Chg. Net New Orders Machine Tool Industry
100
80
% Change, Year to Year
60
40
20
0
1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991
-20
-40
-60
-80
"Upstream Volatility in the Supply Chain: The Machine Tool Industry as a Case Study,"
E. Anderson, C. Fine & G. Parker Production and Operations Management,
Vol. 9, No. 3, Fall 2000, pp. 239-261.
Source: Fine, MIT
What are TRM essentials?
•
•
•
•
•
Performance indicators
Innovations over time, trendlines
Physical limitations
Value Chains
Industry Structure
…
Benefits of MIT Tech
Roadmapping
• Observing Value Chain Evolution over time
• Language for discussion between management &
technology world
• Structured basis for interaction Cross Value Chains,
between academia & industry, spanning basic
research through application
• Bridging between vertical “silos” of research – e.g.
MicroPhotonics  LIDS  Media Lab  eBiz
Center
• Publishing Collaborative Tech Roadmaps
– Risk goes down, Capital Investment goes up (generally)
Other Roadmapping Efforts
• ITRS – International Technology
Roadmapping for Semiconductors
– http://public.itrs.net/
• Electricity Technology Roadmap
– http://www.epri.com/corporate/discover_epri/road
map/
• Steel Industry Technology Roadmap
– http://www.steel.org/mt/roadmap/roadmap.htm
• Lighting Technology Roadmap
– http://www.eren.doe.gov/buildings/vision2020/
• Robotics & Intelligent Machines RM
– http://www.sandia.gov/Roadmap/home.htm
Technology AND Industry
Roadmaps
• Not just focus on technologies
• Which technology gets adopted is often
determined at the Industry level
• How technology is adopted (or not):
what are economic & business issues
TRM Industry-Benefits
• Economic context for technology
decisions & investments
• Lowering Risks for capital investments
• Not Stalin’s 5-year plans – rather,
coordination & collaboration, co-optition
Components of MIT’s Technology
Roadmapping Effort (are at Least)
1. Business cycle dynamics (e.g., systems dynamicslike models of the bullwhip effect)
2. Industry structure dynamics (e.g., rigorous version
of the double helix in Fine’s Clockspeed book)
3. Corporate strategy dynamics (e.g., dynamicize
Porter-like analyses for players in the value chain)
4. Technology dynamics (e.g., the Semiconductor
Industry Association's roadmap built around
Moore's law)
5. Regulatory Policy Dynamics (e.g. Cross-National,
Cross Sector
Source: Fine, MIT
TRM Value Chain vs Component Dynamics
A
Economic /
Business
Cycle
Dynamics
Industry
Structure
Dynamics
Corporate
Strategy
Dynamics
Customer
Preference
Dynamics
Emerging
Technology
Dynamics
Regulatory /
Policy
Dynamics
B
C
D
E
F
The Fine Helix
DOJ 1984
Telecom Act 1996
Integral/
Vertical
Modular/
Horizontal
1998
Broadband,
Convergence
Niche
Competitors
Market Power
(local carriers)
High
Complexity
2000
Organizational
(and regulatory)
Rigidities
Pressure to
Dis-Integrate
Pressure to
Integrate
Economies of Scope
(single provider, PTN)
Source: Carroll, Srikantiah & Wolters 2000; Telecom.LFM769.Spr00.ppt
Generalizing & Quantifying
Clockspeed
• Benefits to comparing between
Industries
• Looking at Fast Industry Dynamics
– Cross-species Benchmarking
• Quantify & Ultimately Model these
Dynamics, improve theoretical
understanding
Different Degrees of Industry
Aggregation
• Communications Roadmap
– Optical Communications
• MicroPhotonics
– Wireless
• Personal Area Networking
• Cellular G3, G4, G5
• Medical Imaging
– MRI
• Functional MRI
• Nanotechnology
– Precision Engineering
• AFM
– Biological Engineering
• Bacterial Robotics
TRM Technology Domains
(including, but not limited to…)
•
•
•
•
•
•
Established
Semiconductors
Photonics
Genomics /
Proteomics /
Celleomics
Wireless
MEMS
Smart Materials
•
•
•
•
•
•
•
Emerging
Soft Lithography
Neurotechnology
Nanotechnology
Organotechnology
Biological Engineering
Gerontechnology
Autonomous Systems
MIT Emerging Technology Matrix:
http://web.media.mit.edu/~davet/notes/emerging-tech-mit.html
MIT Strategic Technology Thrusts
1. Information Technologies = Ever more
sophisticated computation & communication,
leveraging mind & media.
2. Biomedical Technologies = Medical engineering,
perfecting the health & life sciences.
3. Tiny Technologies = Investigating and fabricating
ever smaller systems, at scales from micro thru
nano
4. Complex Systems = Large scale, socio-political &
econo-technological systems.
5. Developmental Innovations = Appropriate and
leapfrog technologies for tackling challenges in
developing & emerging regions
Richly Interwoven MIT Themes
1. InfoTech
2. BioTech
4. Complex
Systems
3. TinyTech
5. Developmental
Innovations
MIT Matrix
1.
Info
2.
Bio
MIT
Research
LCS/AI,
Media,
eBiz,
Mkting
POPI,
CBE,
Whitehd
, McGrn
Academic
Courses
1, 6, 18, HST,
MAS
BE, 6, 7
Extracurriculars
MIT Alum
Startups
MediaTe BioTinyTech
ch
Strategy
Akamai, Amgen,
Dir’ctHit Biogen
Gen’tec
3.
Tiny
4.
5.
Compl’x Develop’l
MTL,
CEEPR,
ISN,
Sloan, AGS
MicroPht,
MPC
Digital
Nations, TDP,
Globalization,
MISTI
3, 5, 6, 7,
8, 16
SDM, 6, 13,
14, 15, 16,
17, 21
1, 4, 5, 6, 7,
11, 15, 17
Consulting
SEID, ATF
Surface- HP,
Lgx, eink, Raytheon
Angstr’m
AfricaOnline,
Evergreen
Solar
http://web.media.mit.edu/~jpbonsen/MIT-Emerging-Technology-Matrix.htm
http://web.media.mit.edu/~jpbonsen/MIT-Emerging-Technology-Matrix.htm
Core Sloan Themes
Leadership
Effective
Organizations,
Culture-Crafting
Entre- & Intrapreneurial
Leadership
Technology
Entrepreneurship &
Strategy Dynamics
Dynamic,
Networked
Organizations
Innovation
Transformative
Innovations,
Emerging Hard &
Soft Technologies,
Disruptive
Challenges
Developmental
Innovations,
MicroFinance
Global Business
Strategy, Accelerating
International
Development
Global
MIT Sloan
Unifying Strategic Themes
Unifying Strategic Themes
Global
Development
Effective
Leadership
Transformative
Innovations
Finance,
Accounting, &
Economics
Manag’nt Sci,
Functional
Disciplines
Behavioral &
Policy Science
Strat & Org’ns
Classic MIT Sloan Disciplinary Strengths
MIT Sloan
Classic Disciplinary Strengths
Global
Development
Entrepreneurial
Effectiveness
Transformative
Innovations
Finance,
Accounting, &
Economics
Manag’nt Sci,
Functional
Disciplines
Behavioral &
Policy Science
Strat & Org’ns
Classic MIT Sloan Disciplinary Strengths
MIT Sloan Matrix
Unifying Strategic Themes
MIT Sloan Capabilities
Global
Development
Sloan
Matrix
Effective
Leadership
Transformative
Innovations
Finance,
Accounting, &
Economics
Manag’nt Sci,
Functional
Disciplines
Behavioral &
Policy Science
Strat & Org’ns
Classic MIT Sloan Disciplinary Strengths
Unifying Strategic Themes
Sloan Matrix
Global International
Development Mgt
Effective Financial
Leadership Engineering,
Management
Transformative
Innovations
Innovation
Leadership
Venture
Finance
Finance,
Accounting, &
Economics
Global Value
Chains,
TechMaps
Entrepreneurial
Policy
Business
Dynamics
Tech-Biz
Ventures
Virtual
Customer
Tech
Strategy
Manag’nt Sci,
Functional
Disciplines
Behavioral &
Policy Science
Strat & Org’ns
Global
Classic MIT Sloan Disciplinary Strengths
Mapping Sloan Faculty to MIT’s
Emerging Strategic Tech Sectors
1. Info
Tech
Strategy
MTIE
Org/HR
Finance
Marketing
Operat’ns
Prod Dev
2. Bio
Tech
3. Tiny
Tech
4. Comp’x 5. Develop’t
Systems
Innovations
Faculty Interests @ Levels of
Analysis
Economy
Economic
Growth
Global
Supply Chains
Global
Strategy
Geography
Sector
Market
Differentiation
Technology
Roadmaps
Technology
Strategy
Market/
Tech
Firm
Venture
Capital
Business
Dynamics
Entrepreneurial
Culture
Organization
Group
Valuing
IP
MarketingEngineering Links
Group
Dynamics
Trader
Psychology
Buyer
Decision-Making
Inventor
Ethos
Individual
Theme
Idea
Levels x Discipline
Finance,
Accounting, &
Economics
Manag’nt Sci,
Functional
Disciplines
Behavioral &
Policy Science
Strat & Org’ns
Economy
Economic
Growth
Global
Supply Chains
Global
Strategy
Geography
Sector
Market
Differentiation
Technology
Roadmaps
Technology
Strategy
Market/
Tech
Firm
Venture
Capital
Business
Dynamics
Entrepreneurial
Culture
Organization
Group
Valuing
IP
MarketingEngineering Links
Group
Dynamics
Trader
Psychology
Buyer
Decision-Making
Inventor
Ethos
Individual
Theme
Idea
Research Clusters
At Various Levels of Analysis…
Economy
Sector
Firm
Group
Individual
Geography
Technology Roadmap
Technology Venture
Observatory
OpenSource
Initiative
Virtual Customer
Initiative
Emerging Tech-Biz
Live Cases
Market/
Tech
Organization
Theme
Idea
Weaving together Interest Clusters
at Various Levels of Analysis…
Economy
Geography
Technology Roadmap
Sector
Firm
Technology Venture
Observatory
Group
Individual
ION
OpenSource
Initiative
Virtual Customer
Initiative
Emerging Tech-Biz
Live Cases
Market/
Tech
Organization
Theme
Idea
Innovation Observatories:
Further Possibilities
Economy
Sector
Firm
Group
Individual
Global Development
Observatory
Technology Roadmap
Venture Capital
Observatory
Technology Venture
OpenSource
Observatory
Initiative
Creative Communities Observatory
Virtual Customer
Initiative
Social Network
Observatory
Emerging Tech-Biz
Live Cases
Decision Neuropsychology Lab
Geography
Market/
Tech
Organization
Theme
Idea
Innovation Observatories:
Technology Roadmapping
Economy
Sector
Geography
Technology Roadmapping
Market/
Tech
Firm
Organization
Group
Theme
Individual
Idea
http://mph-roadmap.mit.edu/
Proposed MIT Communications Roadmap
Consortium
MPC, MTL
MATERIALS &
PROCESS EQUIP
•Silicon
•Gaas
•InP
•Polymers
•Steppers
•Etchers
•MEMS
•Insertion
•Etc..
COMPONENTS
•Lasers
•Amplifiers
•Transceiver
•Filters
•Processors
•Memorys
•Fiber
•ASICS
•MEMS
•DSP’s
•Etc..
LIDS, RLE
EQUIPMENT
MAKERS
•Routers
•Switches
•Hubs
•Base
Stations
•Satellites
•Servers
•Software
•O/S
•Etc..
eBusiness,
Oxygen,
Media Lab
LCS
ITC
NETWORK
OWNERS
•Wireless
•Backbone
•Metro
•Access
•Substations
•Satellites
•Broadcast
Spectrum
•Communic
Spectrum
•Etc..
SERVICE
PROVIDERS
•Long distance
•Local Phone
•Cellular
•ISP
•Broadcast
•Hot Spots
•Cable TV
•Satellite TV
•VPN’s
•MVNO’s
•Etc..
CONTENT
& APPLICS
•Music
•Movies
•Email
•VoIP
•POTS
•Shopping
•ERP
•SCM, CRM
•Surveillance
•eBusiness
•Etc..
DEVICES
•Computers
•Phones
•Media
Players
• Cameras
•PDA’s
•Weapons
•Etc..
END
USERS
•Business
•Consumer
•Gov’t
•Military
•Education
•Medical
•Etc..
Source: Prof. C. Fine, MIT
Why Value Tech
Roadmapping?
• Trends -- Statement of historic performance
improvement and extrapolations into future
• Consensus – Shared opinion about likely
future developments
• Commitment -- Shared willingness to pursue
particular technologies
• Co-Investment -- Basis for agreement on
pre-competitive research funding
• Understanding -- Method of understanding
broader socio-economic context of broad
technology trends
15.795 Technology Roadmapping
(An example Masters Research Seminar)
Professor Charlie Fine, TA Joost Bonsen
Fall 2002
This seminar will explore the purposes and development of
Technology Roadmaps for systematically mapping out possible
development paths for various technological domains and the industries
that build on them. Data of importance for such roadmaps include rates of
innovation, key bottlenecks, physical limitations, improvement
trendlines, corporate intent, and value chain and industry
evolutionary paths. The course will build on ongoing work on the
MIT Communications Technology Roadmap project, but will explore other
domains selected from Nanotechnology, Bio-informatics,
Geno/Proteino/Celleomics, Neurotechnology, Imaging & Diagnostics,
etc. Thesis and Special Project opportunities will be offered.
TRM Class Goals
• Collaborative efforts between 1-3 students,
MIT researchers, & Industry Sponsors
• Across MIT research areas
• Cross Industry Benchmarking
• Partnered with Industrial Sponsors
• Attract students passionate about technology
sector, however broadly or narrowly defined
• Committed to producing coherent & complete
Tech Roadmap (Draft 1.0) during Fall
Semester
Engaging Masters Students in
MIT Sloan Research Agendae
•
•
•
•
Business school disconnect
Unfortunate and sub-optimal
We’re prototyping a new path
Help show that it works!
Seminars & Conferences
• Part of 9 units is required attendance of
relevant technology seminars
throughout MIT.
• Find them through http://web.mit.edu
Google & so forth. Plus Word-of-Mouth.
High TRM Student Expectations
• Serious commitment of time & interest
• Literature review & substantial interviews
• Attend talks & seminar series in that tech
sector, that’s part of the course
– E.g. http://web.mit.edu/mphotonics/www/semseries.shtml
• Data gathering & presentation smithing
• Crafting a draft PPT & DOC by semesters
end
TRM Academia Speakers
•
(and Labs to Engage)
Marty Schmidt, MTL / MEMS
– http://www-mtl.mit.edu/mtlhome/
•
Bruce Rosen, Martinos / NeuroMRI
– http://hst.mit.edu/martinos/
•
Bob Brown & Alice Gast, MIT’s Research Directors
•
Ned Thomas, Soldier Nanotech
– http://web.mit.edu/newsoffice/nr/2002/isnqa.html
•
Eric Lander, Whitehead / Genomics
– http://www.wi.mit.edu/news/genome/lander.html
•
Bob Langer, Biomaterials, Drug Delivery
– http://web.mit.edu/cheme/langerlab/langer.html
•
Victor Zue & Rod Brooks, LCS/AI Labs, Project Oxygen
– http://www.lcs.mit.edu/ & http://www.ai.mit.edu/ & http://oxygen.lcs.mit.edu/
•
Doug Lauffenberger, Biological Engineering
– http://web.mit.edu/be/
•
E. Sachs, 3D Printing
– http://web.mit.edu/tdp/www/
•
Neil Gershenfeld, Media Lab / Ctr Bits & Atoms
– http://cba.mit.edu/
•
Tom Knight, AI Lab / Computation & Biology
– http://www.ai.mit.edu/people/tk/tk.html
TRM Seeds Working
Collaborations w/ MIT Labs &
Sponsors
• Generalizing beyond MicroPhotonics
Center & Communication Roadmap
• Engaging Lab Directors as speakers in
15.795 TRM seminar
– Ask them to speculate about the important
trends in their areas & to proto-roadmap
– What would they like? What would their
sponsors like?
TRM Literature
• MicroPhotonics Center
– http://mph-roadmap.mit.edu
• Example Theses
– http://mitsloan.mit.edu/research/clockspee
d/main.html
• References
– http://www.sandia.gov/Roadmap/
Fin
Joost Bonsen jpbonsen@alum.mit.edu