A few personal thoughts on how to think about VC investment themes, and some detail on a few themes I think are particularly interesting right now.

1. Thinking about themes
Gil Dibner
Partner, DFJ Esprit LLP
@gdibner | gil.dibner@dfjesprit.com | www.dfjesprit.com
http://yankeesabralimey.tumblr.com/

2. What is a VC investment theme?
• A unifying idea that underlies the investment thesis for
multiple potential investments
• Each theme arises from a set of “drivers”
• Theme gives rise to a set of “opportunities” – a sub-grouping
of potential investments
• Broad enough to capture a meaningful portion of an
individual’s/firm’s activities (perhaps 5%-30% at any given
time)
• Narrow enough to serve as effective filters and hang together
tightly as an area of expertise
• One investment may reflect multiple themes
Drivers
(eg. proliferation of
smartphones)
Themes
(enterprise mobility)
Opportunities
(BYOD management,
app mobilization)
Investments
(MobileSpaces,
Enterproid)

3. How would we (loosely) score a theme?
Category of
assessment
Individual
investment criteria
Theme assessment
criteria Examples
People
Existing team’s abilities to execute?
Ability to recruit necessary talent?
How difficult is it to recruit talent
within this thematic area?
Experienced data scientists are
expensive and difficult to find.
Technology
Technological barriers to entry?
Technological significance?
Roadmap development risk?
How significant is technology to
customers and acquirers in this
area?
Technological factors are significant
value drivers for database
customers and acquirers.
Market potential How big is the specific opportunity?
How big is the aggregate set of
opportunities within the theme?
The financial sector is a major
component of GDP that has not
been sufficiently brought online.
Ability to penetrate
Strategy for winning initial
customers and generating
credibility?
Do industry dynamics allow start-
ups to capture market share from
incumbents?
Innovators in the offline retail
technology industry face very long
sales and deployment cycles.
Ability to scale
Strategy for replicating revenue,
economies of scale, and margin
leverage?
Do industry dynamics allow start-
ups to scale revenues and expand
margins?
Data aggregators benefit from
economies of scale and significant
margin leverage.
Exit outlook IPO viability and likely acquirers?
What is the history of IPOs & M&A
in the space? Are there many active
acquirers?
Lack of broad base of acquirers in
the developer tools market.
Geography
Where does the company need to
be located in order to maximize
success?
How does this theme map to a
particular geography’s HR pool and
tech eco-system?
Fraud detection companies in Israel
can draw on a very deep talent pool.
Valuation
Potential for venture returns given
investment valuation?
Where is the theme on the hype
cycle? Is it over-invested or under-
invested?
Hadoop/NoSQL has been massively
over-invested over the past 3 years.
Timing
Is the venture’s roadmap in sync
with the market’s maturation
trajectory?
Is the market ready / almost ready
for companies of this category?
Increased cord-cutting and online
video explosion may drive jump in
interactive video advertising.

4. Applying the hype cycle to VC investment themes
Time
Expectations
Technology
trigger
Peak of
over-
investment
Trough of
disillusionment
Slope of
enlightenment
Plateau of
rationality
Descent into
irrelevance
Digital Society
Online Finance
BI Infrastructure
Data
Science
Data
Pipeline
Software is eating
the world
Mobility
Cloud
infrastructure
E-Commerce
New advertising
battlegrounds
Sustainability
Education
Legal tech
Pervasive
computing
Reinvention
of retail
PV generation
technologies
Social media
monitoring
Heightened
valuation risk
Heightened
general risk Unlikely to
generate
return
Zone of
balanced
risk/return
3D printing

5. A framework for scoring themes
• Generalizations upon generalizations – but potentially directionally useful
• Offers a general sense of potential headwinds and tailwinds faced by companies in each theme
Theme
Ease of
recruiting
talent
Potential for
technical
barriers
Typical
opportunity
size
Ability to
penetrate
Scalability
of models
Exit
potential (#
acquirors)
Hype cycle
status &
maturity Overall
Cloud infrastructure +1 +1 +1 +1 4
Online finance +1 +1 -1 +1 +1 +1 4
Mobility +1 +1 +1 3
BI Infrastructure -1 +1 +1 +1 2
Digital society +1 +1 2
Data pipeline -1 +1 +1 +1 -1 1
Data science -1 +1 +1 +1 -1 1
New advertising battlegrounds +1 1
Software is eating the world +1 -1 +1 +1 -1 -1 0
E-commerce +1 -1 +1 -1 +1 -1 0
Reinvention of Retail -1 -1 +1 -1
Sustainability +1 +1 -1 -1 -1 -1
3D Printing / Hacking hardware -1 +1 -1 -1 -2
Legal services -1 +1 -1 -1 -2
Pervasive computing -1 +1 +1 -1 -1 -1 -2
Education -1 -1 -1 -3

6. SaaS/Cloud Infrastructure
Commoditization of
hardware and IT
stack management
Meaningful cost, time
savings associated
with on-demand
infrastructure
Digital native
employees look to
cloud services
naturally
Cloud security
concerns transformed
from barrier to
opportunity
Secular trends
towards
infrastructure
abstraction and
hybrid architecture
Cloud security
Cloud-based IT
service providers
Cloud-based business
infrastructure
Cloud IT management
solutions

7. Online Finance
Digital natives willing
to trust online
challenger brands.
Growing volumes of
social data available
online
Existing fee structures
too high to be
sustainable; fraud
costs remain high
Financial products are
an ideal “digitally
delivered” service.
Increasing
centralization and
automation of
financial controls and
processes.
Digital banking,
payments, & wallets
Innovative asset
management and
insurance companies
Fraud & credit
analytics
Digitally enabled
credit: lending &
factoring
New currencies and
value-stores
(Bitcoin?)

8. Mobility
Proliferation of
mobile devices and
operating systems
Drive towards
outsourcing and
porous enterprise
boundaries
Mobile device is
becoming a preferred
data consumption
device
Consumerization of IT
by digital native
generation
Increasingly mobile
workforce operating
from home and from
the road
Enterprise application
mobilization
Website mobilization,
refactoring
BYOD / mobile device
management
Dedicated mobile
security providers

9. The digital society
Growing population
of digital natives
Rising structural
unemployment,
particularly among
youth
Coding and web admin
becoming second
languages
Online trust:
Willingness to
communicate,
transact, and relate
via digital means
Societal trend
towards self-reliance,
entrepreneurship,
and “making.”
Everyone is a web
master, e-commerce
shop owner
The P2P economy
Enabling digital cottage
industries
The maker movement
Digital intimacy and
relationships

10. The Data Pipeline
Enterprises are
increasingly
leveraging structured
data from multiple
3rd party sources
Massive quantities of
data exist
unstructured on the
public web
Storage is getting
cheaper, but preparing
data for analytical
applications remains a
challenge
Business users
increasingly demand
access to data and
analytics
Data complexity
keeps rising
Dataset creation
tools & platforms
Data marketplaces Data integration
API management
tools
Next-generational
departmental and
enterprise reporting
and visualization

11. Data Science
New sources of data:
APIs, public web,
social data, etc.
Cheaper storage and
compute
Data analytics is in
fashion
Proliferation of
analytical DBs
Success of data-
driven businesses
Data science as a
service
Democratization:
Making it easier for
more users to apply
data science.
Verticalization:
Industry-specific
applications of data
science techniques
Machine learning
platforms
Embedded data
science applications

12. New advertising battlegrounds
Proliferation of
smartphones, tablets,
smart TVs, wearable
computing, and cord-
cutting.
“Online” attention
fragmenting across
identities /devices
Proliferation of “walled
garden” online
environments (istore)
& failure of traditional
tracking tech.
Increasing new data
types (location,
usage, social, etc.)
and analytical power
Inevitable shift of
brand-oriented
advertising online
Interactive television
and TV advertising
Statistical attribution
Automated campaign
and landing page
optimization
Traffic arbitrage

13. “Software is eating the world”
Increasing number of
enterprises and
individuals are
writing code
Commoditization of
basic (cloud)
computing
infrastructure
Recognition that
“software/IT” can
drive value creation
across many industries
Continuous
deployment &
integration are
widespread
Greater use of open-
source and third-
party code & binaries.
CI/CD/Devops: Tools
to help deploy code
faster, better,
cheaper
Developer tools::
Tools to help
developers create
value faster
Analytics:
“BI for the software
production process”

14. Reinvention of (Online/Offline) Retail
Ubiquity of
smartphones; e-mail,
and other digital
channels
Consumers expect
personalization
Online retail taking
greater wallet share
Availability of big data
analytics
Every physical retailer
is now an online
retailer as well
Highly personalized
CRM
Enhanced in-store
experience
Next-generation
loyalty programs
Next-gen point of sale Social commerce

15. Sustainability
Expanding global
middle class with
higher expectations
Widespread
recognition of
sustainability and
environmental issues
Rising commodity
prices
Increased consumer
interest in organic
and locally sourced
food
Approach of grid
parity in some
alternative energy
areas
Agricultural efficiency
SW
Food-tech: New food
production
technologies and
delivery systems
Locally-sourced food
retail
Renewable
generation tech
Power consumption
efficiency
technologies and
solution

16. Pervasive Computing
Rapid prototyping
and crowd-funding of
hardware
WiFi and GSM
connectivity is
everywhere
Sensors and processors
are getting more
varied and cheaper
Consumers and
workers are carrying
powerful devices with
them everywhere
Manufacturers
increasingly seek the
benefits of devices
that “phone home.”
Infrastructure for the
“Internet of things”
Networked Consumer
Electronics
Wearable computing,
quantified self
Smart cars, drones,
and other vehicles
Connected home