1. The Hypothesis-Driven Business
The Research Board 02.25.15
Confidential and Proprietary - Not for Distribution

2. Confidential and Proprietary - Not for Distribution 2
Background
• Managing Partner of IA Ventures, a $155M venture firm
focused on creating competitive advantage through data
o Lead-managed companies include Datasift, Digital
Ocean, MemSQL, Simple and Transferwise
• 5 years as a professional angel investor
o Early investor in Buddy Media (SalesForce), Invite Media
(Google), Magnetic, TubeMogul (IPO) and TweetDeck
(Twitter)
• 18 years on Wall Street (Citi, Deutsche) in Capital
Structuring, Derivatives and Quantitative Trading

3. • The key to unlocking data’s value is through rigorous
hypothesis development and testing
• But before you can ask questions, the data needs to be
in the right form
• Data Strategy = Business Strategy
• These principles apply not only to startups but multi-
nationals as well
Confidential and Proprietary - Not for Distribution 3
Beyond Buzzwords

4. Data is:
● Easier to access (proliferation of APIs)
● Cheap(er) to process and store (cloud)
● The beneficiary of better tools for
business analysis (DSaaS)
● More easily actionable in (near) real-
time (feedback loops, machine learning)
Confidential and Proprietary - Not for Distribution 4
Evolution of the Data-Driven Business

5. ● The best founders think deeply about what they are
trying to prove, and tie these hypotheses to core
business metrics
● This creates a data-driven culture that fuels critical
insights and permeates everything they do
● This extends into how they think about their natural
data assets as well as the metadata that can be
extracted for important business decisions
● This requires coordination among and commitment
from many constituencies across the organization:
Operations; Development; Product; Sales; and Senior
leadership
Confidential and Proprietary - Not for Distribution 5
Hypothesis Development

6. ● Virtually every startup (and every company) has data
as a key strategic asset
● While not all businesses have streaming data-at-scale,
even “small data” needs to be managed well for
extracting maximum value
● Thoughtful architecting of the data environment
upfront can save huge amounts of pain further down
the road
● The proliferation of low-cost on-demand tools has
brought institutional-grade infrastructure within reach
of the small enterprise
Confidential and Proprietary - Not for Distribution 6
Data Enablement

7. ● Almost all of the businesses we invest in are building
“platforms”
● Founders almost always focus on a single high-value
use case to prove the value of the platform: general
platform sales are “out”, while specific product sales
are “in”
● Refining the first product to ensure tight
product/market which demonstrates the power of the
platform is key
● Creating matrix organizations that support investment
in both the platform and the products is essential for
innovation - and survival
Confidential and Proprietary - Not for Distribution 7
Platforms for Profit

8. ● What are some new opportunities for
data-driven business models?
● How can data be used to drive
competitive advantage?
● Can data be used to secure barriers to
entry?
Confidential and Proprietary - Not for Distribution 8
The Big Questions

9. ● 2-sided markets (CareGuardian,
NewsCred)
● Contributory databases (BillGuard,
Metamarkets)
● Turning 3rd party data into 1st party
data (The Trade Desk, Transferwise)
EACH OPPORTUNITY LEVERAGES DATA FOR COMPETITIVE
ADVANTAGE AND CREATES BARRIERS TO ENTRY
Confidential and Proprietary - Not for Distribution 9
New Opportunities for Leveraging Data