Introductory Keynote on Deep Tech in Europe presented by Richard Muirhead at the inaugural OpenOcean Annual CEO Summit 2017 in London

1. A N N U A L C E O S U M M I T 2 0 1 7
Deep Tech Gets Delicious
London, 4th April 2017
t: @richardmuirhead
#OOS17
t: @openoceanvc

2. The world is dangerous, volatile & polarised
“Success in creating
AI would be the biggest
event in human history.
Unfortunately, it might
also be the last.”
– Stephen Hawking, 2014
“Millennials ... first to
earn less than previous
generation”
– The Guardian, 2016
“Apocalypse is 30
seconds closer, say
Doomsday Clock
scientists”
– The BBC, 2017
“Indeed, in an
increasingly unstable
world … we face the
same global threats from
terrorism & extremism”
– Theresa May, UK PM, 2017

3. In 200 yrs, humanity has tamed ‘famine, plague and war’
Extreme Poverty
Basic Education
Literacy
Democracy
Vaccination
Child Mortality
6% not living in
extreme poverty
94% living in
extreme poverty
83% have not attained
any education
17% have basic
education or more
88% are not able
to read
12% are able
to read
90% not living in
extreme poverty
10% living in
extreme poverty
14% have not
attained any
education
86% have basic
education or more
15% are not able
to read
85% are able
to read
against diphtheria, pertussis (whopping cough), and tetanus
99% not living
in a democracy
1% living
in a democracy
0 vaccinated
57% survive the first
5 years of life
43% die before they
are 5 years old
44% not living
in a democracy
56% living
in a democracy
86% vaccinated
96% survive the first
5 years of life
4% die before they
are 5 years old
14% not vaccinated
1820 1840 1860 1880 1900 1920 1940 1960 1980 20002015
1820 1840 1860 1880 1900 1920 1940 1960 1980 20002015
1820 1840 1860 1880 1900 1920 1940 1960 1980 20002015
1820 1840 1860 1880 1900 1920 1940 1960 1980 20002014
1820 1840 1860 1880 1900 1920 1940 1960 1980 20002015
1820 1840 1860 1880 1900 1920 1940 1960 1980 20002015
Note: With credit to Yuval Harari, Homo Deus and GlobebyNumbers 2015

4. Data drives deployment phase of the knowledge age
The scarce resource began with
Food, to Land, Oil, Capital and now
to Attention
“Innovation is the central issue
in economic prosperity”,
Michael Porter, Harvard Business
School
Innovation
1770 1820 1870 19701920 2020
The Industrial
Revolution
Age of Steam and
Railways
Age of Steel and
Heavy Engineering
Age of Oil, Autos and
Mass Production
The ICT Revolution
Recessions
Canal Mania Great British Leap
Railway
Mania
The Victorian
Boom
Global market
infra. build-up
Belle Epoque
Progressive Era
The Roaring
Twenties
Post-war
Golden Age
Dotcom and
Internet Mania
The Knowledge Age
Note: With credit to Carlotta Perez

5. Deep tech reinforces society’s move into knowledge era
The New Interface
Mobile, Multi Device, Multi Platform –
The world is being wired, mostly wirelessly
Cloud Computing
Infinite cheap storage, CPU, GPU,
communications. The API economy,
IaaS, Multiplicity of PaaS platforms.
Genomics
The Intersection of digital software and
biological software
Data Management
Decentralization, Data Security, Data-bases:
From Navigational to Relational to Distributed to Decentralized.
Data Analytics, ML & AI
From data visualisation to prediction
algorithms to deep learning to AI
4th Industrial Revolution
IoT, Robotics, Manufacturing
Note: OpenOcean Analysis

6. The ‘Technaissance’ of the EU City State
Deepmind
King
Rightmove
Fleetmatics
Shazam
Transferwise
Funding Circle
Deliveroo
MicroMuse
Cambridge
Oxford
Imperial
Skyscanner
Zendesk
Adyen
MySQL, Supercell, Spotify, Truecaller
Skype
e-Residency
Zalando
HelloFresh
Soundcloud
Auto1
TU Munich
KIT
RWTH
Avast
Mindmaze
ETH Zurich
EPF Lausanne
This is the Post Silicon Valley Era! 6
Blablacar
Criteo
Business Objects
Polytechnique
ENS

7. 52
43
31
20
16
11
5
2211100000
20142013 20162015200520042003200220012000 2012200820072006 20112009 2010
EU tech results are starting to roll in
European Billion dollar
companies are valued
at 18x revenue
compared to 46x in
the US (GP
Bullhound, 2016)
# of European $B + companies founded since 2000, by year first surpassed $B + milestone
Note: OpenOcean Analysis. Several companies that were formerly valued above $B+ have since seen their valuations officially fall below that level, incl. e.g., Home24, Monitise and Powa Source: GP Bullhound & Atomico research

8. From ‘time to download’ to ‘time-to-love’
Top 20 US Unicorns, First Equity Financing to $1B+Valuation
Valuation(M)
$1,000
$900
$800
$700
$600
$500
$400
$300
$200
$100
$0
0 1 2 3 4 5 6 7 8 9 10
Years from first Equity Financing
: ‘delicious’

9. Assembling the ingredients
Killer
Team
Massive
Market
‘Delicious
Product’
Growth Hacking
Purpose & Play [CEO]
Attract & Retain [CEO]
Architect & Innovate [Engineering & Product]
Package & Promote [Product & Marketing]TIDE
Teach & Close [Sales & Marketing]
Measure & Manage [Management]OKR
'Deep
Tech'
& ‘scale-hacking’

10. Deployment: entire industries are being re-imagined
Healthtech Industry
The software in our bodies is
beginning to be re-programmed but
the software in our computers
Financial Services
The battle for the customer and the
unbundling of the bank
The Workplace
Enabling small businesses to out
race large corporations
Mobility & Transport
The dawn of autonomous vehicles
will fundamentally restructure
modern cities
Media & Entertainment
Hyper-personalisation and the
loss of privacy
The IT Industry itself
The time has come to please the
developers: They are the new
Kingmakers

11. 40%
30%
20%
10%
60%
50%
The oil barons give way to the data kids of Silicon Valley
The largest companies by market cap. The oil barons have been replaced by whiz kids of Silicon Valley
Top 10 publicly traded companies (by Market cap) Tech Other
S&P 500 Sector Weightings – IT
0%
1991 1692 93 94 95 96 97 98 99 2000 01 02 03 04 1514131211100908070605 403938373635343332313029282726252423222120191817
Note: OpenOcean & McKinsey Analysis 2017

12. Bottom 50% of income earners
Top 1% of income earners
Dangerous inequality from tech-amplified capitalism
Inequality, share of U.S. pre-tax income for 50 percent and top one percent of earners, 1962-2014
Sources: Thomas Piketty, Emmanuel Saez and Gabriel Zucman, 'Distributional National Accounts: Methods and Estimates for the Unites States,' 2016, Cambridge, MA: National Bureau of Economic Research
Note: The unit is the individual adult and incomes within married couples are split equally.
10
12
14
16
18
20
%
1962 1971 1980 1989 1998 2007 2016

13. That’s why we need your attention today please!
Workplace
Purpose + Play (workshop)
Sales (workshop)
Machine Learning
Databases
Attention + Privacy
User Growth (workshop)
Deep Tech
Industries
Scale Hacking
Data meets designDelicious
Wrap up

14. A N N U A L C E O S U M M I T 2 0 1 7
#OOS17
t: @openoceanvc
Deep Tech Gets Delicious
London, 4th April 2017
t: @richardmuirhead