Searching for Entrepreneurial Opportunities:

Rates of Improvement and Economic Feasibility

Jeffrey L Funk

Division of Engineering and Technology Management

National University of Singapore

Where Should we Search?Should we search for opportunities in specific

technologies? industries? customers?Should we read specific newspapers,

magazines, or websites to find opportunities?Should we listen to the experts?Should we focus on change? Should we just follow our own

interests?passions?

Change Provides Opportunities

It provides opportunities for new products and services It also provides opportunities for new firms

New entrantsIncumbents with low shares

Types of changesTechnologyPolitical and regulatory rulesSocial and demographic factorsIndustry structure

Looking at this Change in More Detail Technology

Magnitude of change is important

General changes (Integrated Circuits, magnetic storage, Internet) provide more opportunities than do changes in special technologies

Political and regulatory rules Licenses

Environmental and safety rules

Social and demographic factors Changes in customer taste

Increased incomes

Demographic changes such as more women in the workforce or longer life spans

Industry structure Vertical disintegration

Lower capital intensity

Example of How Changes Led to Entrepreneurial Opportunities in Personal Computers

Opportunity (Personal Computers in 1970s, including software and components)

Social: more income and more knowledgeworkers at home or in small businesses

Economic: greater need for processing information

Industry structure: more vertical disintegration in computer industry

Technology: falling cost and rising performance of integrated circuits (ICs) and magnetic storage

Many Types of Entrepreneurial Opportunities Emerged for Personal Computers

Manufactures of Integrated circuits (ICs) Hard disks Compact disks (CDs) Displays Other sub-assemblies

Design houses for integrated circuits (ICs) Software suppliers Contract manufacturers for PCs and sub-assemblies Changes in higher level systems such as retail, logistics, finance,

manufacturing, insurance, and health care

Since we are Engineers, Let’s Focus on Technological Change

Technological change makes new things technically and economically feasible (and often leads to higher incomes)

Most venture capital is in industries with lots of technological change

Other types of change are also important, but receive less emphasis today

There are patterns of technological change that enable us to understand when new technologies might become economically feasible

How can we Understand Technology Change?

Should we read specific newspapers, magazines, or websites to find opportunities?

Should we listen to the experts?

Let’s look at some predictions made my MIT’s Technology Review

The Context MIT’s Technology Review produces a list of 10

breakthrough technologies each year (2001, 2002-2014) “We have chosen 10 emerging areas of technology that will

soon have a profound impact on the economy and on how we live and work”

“The mission of MIT Tech Review is to equip its audiences with the intelligence to understand a world shaped by technology”

These lists are based on conversations with academic experts from a variety of scientific disciplines predictions were based on the “educated predictions of our

editors (made in consultation with some of the technology’s top experts)”

The Context (2)

In July 2014, I gather recent market sales data for the predictions done in 2001, 2003, 2004 and 2005

This was done by Googling market, size, and sales for each technology, sometimes changing the name of the technology or

broadly defining it in order to find data

Reports by market forecasting companies were major sources of data

The Basic Conclusion After excluding 7 technologies that were too broad to gather data,

there were 33 technologies 1 has greater than $10 Billion in sales

power grid control (smart grids)

2 have sales between $5 and $10 Billion micro-photonics (photonic crystals), personal genomics

11 have sales between $1 and $5 Billion Grid computing, Molecular imaging, Synthetic Biology, Distributed

Storage RNAi Interference, Brain-Machine Interface, Data mining, Biometrics Digital Rights Management, Natural Language Processing, Microfluidics

5 have sales between $100 million and $1 Billion 14 have sales less than $100 million

How Good were these Predictions?

Difficult to assess, but More than half still have small markets of

less than $1Billion in sales Might these markets grow in the near future? Or have they been abandoned? Did MIT’s Technology Review miss any

technologies that have become big markets in the 21st century?

Some Big Markets that Have Emerged in the 21st Century

Smart Phones: $335 Billion in 2013 Cloud Computing: $110 billion in 2012 Tablet Computers: $61 billion in 2012 Big Data: $11.6 Billion in 2012 Social Networking: Facebook had revenues of $7.8 Billion

in 2013 eBooks and readers: >$5 billion just in the U.S. for

Amazon Adjusting for global markets, these technologies have

larger markets than $10B, which is larger than 33 of the 34 technologies chosen by MIT

What Technologies were Chosen in Place of the Big Markets?

2005

Airborne Networks

Quantum Wires

Silicon Photonics

Metabolomics

Magnetic-Resonance Force Microscopy

Universal Memory

Bacterial Factories

Enviromatics

Cell-Phone Viruses

Biomechatronics

2004

Universal Translation

Synthetic Biology

Nanowires

T-Rays

Distributed Storage

RNAi Interference

Power Grid Control

Microfluidic Optical Fibers

Bayesian Machine Learning

Personal Genomics

2003

Wireless Sensor Networks

Injectable Tissue Engineering

Nano Solar Cells

Mechatronics

Grid computing

Molecular imaging

Nanoprint lithography

Software assurance

Glycomics

Quantum cryptography

2001

Brain-Machine Interface:

Flexible Transistors

Data Mining

Digital Rights Management

Biometrics

Natural Language Processing

Microphotonics

Untangling Code

Robot Design

MicrofluidicsOrange: <$100 Million salesBlue: too broad and vague to gather data

How could this have Happened? Why did MIT’s Technology Review choose these esoteric

sounding technologies in 2001, 2003, 2004 and 2005 in place of smart phones, cloud computing, tablet computers, Big Data, social networking, and eBooks?

A good question for fields of cognition and behavioral science MIT is a leading if not the leading engineering university in the

world in top 5 universities each year for startups and licensing income80 Nobel Laureates spent time at MIT

Clearly there are major cognitive biases in predicting breakthrough technologies, even for smart people

Let’s consider one from Daniel Kahneman, Nobel Laureate in Economics

Cognitive Biases: Nobel Laureate Daniel Kahneman

People assess relative importance of issues, including new technologies by ease of retrieving from memory

largely determined by extent of coverage in media

E.g., media talks about solar, wind, battery-powered vehicles, bio-fuels and thus many think they have rapid rates of improvement - but only some are

Second, judgments and decisions are guided directly by feelings of liking and disliking One person invested in Ford because he “liked” their products – but was Ford

stock undervalued?

Many people “like” some technologies and dislike others without considering rates of improvement

Source: Daniel Kahneman, Thinking Fast and Slow, 2011

How Might Kahneman’s Ideas Apply to MIT MIT’s Technology Review didn’t pay attention to popular

media when they made their predictions But, they used their own network of engineers and

scientists, who may be smarter than popular media but nevertheless biased Leading academic engineers and scientists usually

research elemental technologiesemphasize new scientific disciplines or ideasoptimistic about their technologies or those of their colleaguesand thus ignore system technologies (or markets) such as smart

phones, tablet computers, and cloud computing

The upshot is that MIT’s Technology Review chose a wide variety of “ideas,” many of which will never become big markets

Preliminary Conclusions

Don’t ask the experts because they are just as biased as everyone else…..

More research on this issue is needed A more systematic application of cognitive

biases to predictions about breakthrough technologies is needed to understand why predictions aren’t so good

And a more systematic method of predicting breakthrough technologies is needed

Is their a Better Way? Some technologies experience more rapid rates of

improvement than do other technologies (see next slide) Do these rapidly improving technologies or systems

composed from them have a better chance of achieving growth in market size than do other technologies?

For example, have integrated circuit-related technologies (e.g., smart phones) achieved larger market sizes than have other technologies?

Rough Analysis: using a data base on rates of improvement for more than 100 technologies, underlying technologies for predicted breakthrough

technologies (and those on slide 13) and their rates of improvement were identified

See my slideshare account (http://www.slideshare.net/Funk98/presentations), Technology Change and the Rise of New Industries (http://www.sup.org/book.cgi?id=21867) andExponential Change: What Drives it and What Does it tell us About the Future http://www.amazon.com/Exponential-Change-drives-about-future-ebook/dp/B00HPSAYEM

Different Technologies have Different Annual Rates of Improvement

-10 -8 -6 -4 -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

>42

0

5

10

15

20

25

Number of Technologies by Annual Rates of Improvement

Annual Rates of Improvement

Source: Nagy B, Farmer D, Bui Q, Trancik J 2013. Statistical Basis for Predicting Technological Progress. PLoS ONE 8(2): e52669. doi:10.1371/journal.pone.0052669NREL, 2013

67%: <9% per year89%: <15% per year

Rates of Improvement and Breakthrough TechnologiesThe successful breakthrough

technologies (identified by MIT) and those listed on slide 13 (not identified by MIT) depended on technologies with

rapid rates of improvement

Breakthrough Technology Underlying Technologies

Smart phones Integrated Circuits (ICs), DisplaysTablet computing

eBooks and eReaders ICs, Displays, Organic Transistors

Digital Rights Management

ICs

BiometricsMolecular imaging Computers, Photo-sensorsMicrofluidics MEMSMicro-photonics Photonic ICsSmart Grids (power control) Internet bandwidthCloud computing

Big DataSocial NetworkingData mining Internet bandwidth,

ComputersGrid computingNatural Language Processing

Internet bandwidth, Computers

Distributed Storage Internet bandwidth, Mag Storage

Personal genomics DNA SequencingSynthetic Biology DNA SynthesizingBrain-Machine Interface Invasive Neural Interface

Techniques

Technologies Dimensions of Measure Improvement Rate Per Year

Integrated Circuits Number of Transistors Per Chip

38%

MEMS Chips Drops per second 61% Organic Transistors Mobility 94% Photo-sensors Pixels per dollar 49% Photonic ICs Data Capacity per chip 39% Displays Square meters per dollar 11% Magnetic Storage Bits per dollar 39% Computers Instructions per unit time 36% ,QWHUQHW%DQGZLGWK Bits per second 49% Invasive Neural Interface

Simultaneously Recorded Neurons

10.1%

DNA Sequencers Sequencing per unit cost 146% DNA Synthesizers Synthesizing per unit cost 84%

Rates of Improvements for Technologies that Impact on “Breakthrough Technologies”

Cu

rrent

Mark

et

Siz

e

> $10B

>$1B<$10B

< $1B

Rates of ImprovementSlow (<10%)

Rates of Improvement vs. Current Market Size

Fast (>10%)

Smart Grids Smart PhonesCloud Computing Tablet ComputersBig Data Social NetworkingeBooks/readersMicro-photonics, Personal genomics,

Grid computing, Molecular imaging, Synthetic Biology, Distributed Storage, Brain-Machine Interface, data mining, Digital Rights Management, Biometrics, Natural Language Processing, Microfluidics

Wireless Sensor Networks, Flexible Transistors, Bio-mechatronics

Quantum cryptography, T-Rays, Quantum Wires, Silicon Photonics, Universal Memory, Injectable Tissue Engineering, Nano Solar Cells, Nanowires, Microfluidic Optical Fibers, Airborne Networks, Magnetic-Resonance Force Microscopy, Cell-Phone Viruses, Robot Design, Glycomics, Nanoprint lithography, Metabolomics

RNAi Interference

Seems to be a Correlation.. Technologies with faster rates of improvement generally

have larger market sizes>$10B: all 7 had rapid rates of improvement$1B >, <$10B: 10 of 11 had rapid rates of improvement<$1B: 3 of 19 had rapid improvements

But this is just a rough analysisNot easy to identify underlying technologies for all of the

predicted breakthroughsData on all relevant underlying technologies were not foundSome technologies may be experiencing rapid rates of

improvement even though data for them was not found

Getting Back to Searching for Entrepreneurial Opportunities

If rates of improvement are important, what do they tell us about the future and searching for entrepreneurial opportunities? Which technologies currently experience rapid rates? How much improvements are needed before the

technologies or systems composed from them become economically feasible?

Can analyzing these two variables tell us about the future? technologies or systems composed from them becoming

economic feasible And to investigate further to find entrepreneurial

opportunities

Rate of ImprovementExte

nt

of

Impro

vem

en

t N

eed

ed

Small

Large

Slow Fast

Technologies with Rapid Rates of Improvement Will Become Economically Feasible Faster than Will Other Technologies

Now or Probably Very Soon

Probably Never

Within 5 to 15 Years?

Within 5-15 Years?

Technologies Experiencing Rapid Rates of Improvements(Information Transformation)

Technology Dimensions of measure Time Period Rate Per YearIntegrated Circuits Number of transistors per chip 1971-2011 38%MEMS Number of Electrodes per Eye 2002-2013 46%

Drops per second for printer 1985-2009 61%Organic Transistors Mobility 1994-2007 101%Power ICs Current Density 1993-2012 16%Carbon Nanotube Transistors

1/Purity (% metallic) 1999-2011 32%Density (per micrometer) 2006-2011 357%

Superconducting Josephson Junctions

1/Clock period 1990-2010 20%1/Bit energy 1990-2010 10%Qubit Lifetimes 1999-2012 142%Bits per Qubit lifetime 2005-2013 137%

Photonics Number of Optical Channels 1983-2011 39%Computers Instructions per unit time 1979-2009 36%

Instructions per time and dollar 1979-2009 52%Quantum Computers Number of Qubits 2002-2012 107%

Technologies Experiencing Rapid Rates of Improvements(Information Storage)

Technology Dimensions of measure

Time Period Rate per Year

Magnetic Storage Recording density (disks)

1991-2011 56%

Recording density (tape)

1993-2011 32%

Cost per bit 1956-2007 33%Flash Memory Storage Capacity 2001-2013 47%Resistive RAM 2006-2013 272%Ferro-electric RAM 2001-2009 37%Phase Change RAM 2004-2012 63%Magneto RAM 2002-2011 58%

Technologies Experiencing Rapid Rates of ImprovementsInformation Transmission, Materials and Biological Transformation

Technology Domain

Sub-Technology Dimensions of measure

Time Period

Rate PerYear

Information Transmission

Last Mile Wireline Bits per second 1982-2010 48.7%Wireless, 100 m Bits per second 1996-2013 79.1%Wireless, 10 m 1995-2010 58.4%Wireless, 1 meter (USB) 1996-2008 77.8%

Materials Transformation

Carbon Nanotubes 1/Minimum Theoretical Energy for Production

1999-2008 86.3%

Biological Transformation

DNA Sequencing per unit cost 2001-2013 146%Synthesizing per cost 2002-2010 84.3%

Cellulosic Ethanol Output per cost 2001-2012 13.9%

Technologies Experiencing Rapid Rates of Improvements(Energy Transformation and Transmission)

TechnologyDomain

Sub-Technology Dimensions of measure Time Period

Rate Per Year

Energy Trans-formation

Light Emitting Diodes (LEDs)

Luminosity per Watt 1965-2008 31%Lumens per Dollar 2000-2010 40.5%

Organic LEDs Luminosity per Watt 1987-2005 29%GaAs Lasers Power/length-bar 1987-2007 30%LCDs Square meters per dollar 2001-2011 11.0%Quantum DotDisplays

External Efficiency 1994-2009 79.0%

Solar Cells Peak Watt Per Dollar 2004-2013 21.0%Photo-sensors (Camera chips)

Pixels per dollar 1983-2013 48.7%Light sensitivity 1986-2008 18%

EnergyTransmission

Super-conductors Current-length per dollar 2004-2010 115%

How can this Data be Used? To understand reasons for rapid improvements1

To analyze past1,2, current, or future3 changes in specific systems To analyze changes in tradeoffs between different designs at

system level, sub-system level1,2

can this be better done with detailed cost models? For future, to better understand when new forms of designs

might become economically feasible3

To design systems that accommodate future design changes To help students create new businesses that are based on new

technologies or systems composed from new technologies1 Funk, 2013, Technology Change and the Rise of New Industries, Stanford University Press; Funk J 2013 What Drives Exponential Improvements? California Management Review 55(3): 134-152, Spring 20132 Funk J 2009. Systems, Components, and Technological Discontinuities: The case of magnetic recording and playback equipment, Research Policy 38(7): 1079-1216. 3 Funk J and Magee C 2014. Exponential Change: What drives it? What does it tell us about the future?

MRI and CT Scanners Laptops MP3 PlayersCalculators Video Set-top boxes E-Book ReadersDigital Games Web Browsers Digital TV Watches Mobile Digital Cameras Smart PhonesPCs Phones PDAs Tablet Computers

The Past: Increases in the Number of Transistors Make New Forms of Electronic Products Economically Feasible

If we add magnetic disks, new displays, glass fiber, lasers, and photo-sensors

The list of new systems becomes much longerNew forms of Internet content and applications have

become possible over the last 20 yearsMore recently: Big Data, Cloud Computing, Social

Networking

What will be next? What kinds of new systems should system designers be

thinking about? How should this impact on the design of new systems?

For the Future: Students have Done Further Analyses on More than 50 Technologies New forms of

electronic systems: smart homes, robotic exoskeletons, smart grid, 3D scanners, eye tracking, pico-projectors, wireless charging of phones and vehicles, 3D Holography, Ink Jet Printers, light field image sensors, wearable computing, solar gliders for telecom, quantum computers

health care: Bioprinters, bionic eyes, wearable health care devices displays: flexible OLEDs, conformal electronics, transparent displays materials: carbon-nanotubes, aerogels, superconductors, bio-

luminescence, membranes transportation and energy: automated vehicles, dedicated roads for

automated vehicles, electric vehicles, wireless charging, smart grid, drones for transport

These analyses are available here: http://www.slideshare.net/Funk98/presentations

My Analyses and Student Analyses

Helps students understand the tradeoffs in systems between

New forms of designsDifferent technologies

when new technologies or new forms of designs might become economically feasible

which technologies will form the basis for new businesses Many will argue that you can’t predict the future

But all actions assume predictions And assuming no improvements is clearly a worse prediction

than assuming faster improvements in some technologies than in other technologies

What do these Technologies tell us about the Future? No end to Moore’s Law and improvements in MEMS and Bio-

Electronic ICs In combination with the Internet, this is enabling

More Big Data Analysis, Cloud computing, Social Networking Internet of Things and Home Automation Better control of all systems (logistics, factories)

For health care Computer assistants for doctors Mobile phones become the center for health care Drug delivery, Bionic eyes, Exoskeletons, Cyborgs DNA sequencers and synthesizers change drug and materials

development

What do these Technologies…. (2) Human computer interfaces

Better displays including more flexibility and more responsive to touch and voice

Augmented reality, Virtual reality, Wearable computing Food and agriculture

better sensors for global value chains of food (and other products) prescriptive planting and laser leveled fields

Energy Rapid reductions in cost of solar cells (but not in installation costs)

Materials Ultra-thin materials with high strength-to weight ratios Nano-particles and fibers Carbon nanotubes for electronics and other applications

What do these Technologies…. (3)

Did any of the technologies mentioned on the last two slides surprise you?

Maybe none But what about energy?

Wind turbines: 2% rate of improvement per year over last 30 years

Li-ion batteries: 5% rate of improvement over last 20 years

How can these slow rates of improvement make a meaningful contribution to sustainability when they are still far from competitive with existing technologies?Yet the IPCC and sustainability organizations focus on these

technologies

New Systems to Think About and Analyze More efficient logistics for humans and freight through better

computers and RFID tags Roads dedicated to autonomous vehicle (through improvements in

ICs, MEMS, and lasers) can increase road capacity and fuel efficiency Smart grid (through better Internet) can enable more charging

points and a greater frequency of vehicle recharging and thus reduce need for battery storage capacity

Better digital and power (MOSFETS) ICs and thin film coils reduce cost of wireless charging and thus further facilitate frequent recharging and need for battery storage capacity in vehicles

In combination with existing and improved mobile phones, cheaper and better GPS can help vehicles find charging points, cities improve bus service, and commuters increase their use of public transportation

Conclusions Searching for entrepreneurial opportunities is an important task

Has big impact on success of entrepreneur

But how should entrepreneurs search for opportunities? Should they search for opportunities in specific technologies, industries,

customers?

Should they read specific newspapers, magazines, or websites to find opportunities?

Should they listen to the experts? Should they focus on change?

Should they just follow their own interests or passions?

Expert predictions don’t work well because the experts are biased like everyone else

Understanding rates of improvement can help us better find entrepreneurial opportunities

0 2 4 6 8 10 120

2

4

6

8

10

12

14

Figure 2. Number of Chemical Tech-nologies by Annual Rates of Im-

provement

Annual Rates of Improvement

-10 -8 -6 -4 -2 0 2 4 6 8 10 12 140

2

4

6

8

10

12

14

16

18

20

Annual Rates of Improvement

Figure 3. Number of Non-Chemical Technologies by Annual Rates of

Improvement

Focusing on Technologies with Annual Rates Under 15%