The Startup Policy Lab Workspace Case Study 2015 examined the unique characteristics of the startup communities at two leading workspaces in Silicon Valley: Runway Incubator in San Francisco and Hacker Dojo in Mountain View.
Startup policy lab
SPL develops tools to address public
policy driven by emergent technology
Workspace Case Study 2015
Charles Belle and Kathie Chuang
Startup Policy Lab is a fiscally sponsored project of Community Initiatives – a 501c3 nonprofit organization
Startups live, work, and play in
workspaces all over the world.
HackerSpaces, a community generated wiki, lists
over 350 workspaces in the united states
WorkSpaces are increasingly centers
of startup activity, so we wondered:
WHY DO STARTUPS SELECT ONE WORKSPACE OVER ANOTHER?
WHAT ARE THE CAPITAL NEEDS STARTUPS IN WORKSPACES HAVE?
HOW LONG WILL THE STARTUPS USE A WORKSPACE?
WE CONDUCTED ONE ON ONE INTERVIEWS:
SPL spoke with 82 startups using a 10 question survey.
LEVERARGED SECONDARY DATA SOURCES:
One workspace partner shared >200,000 data points
related to membership activity.
WE ENGAGED IN INDEPENDENT RESEARCH:
SPL collected third party data about startups from Angel
List and Crunchbase.
We started by comparing two workspaces
Learn the best ways to collect data about the dynamic startup community
Compare two different types of workspaces to surface initial patterns and differences
Better understand the characteristics of startups within workspaces
Determine if there is sufficient support to launch an annual and more robust study
our goal was to develop the foundation for
more in-depth research
W E F O U N D P A T T E R N S , T A K E A W A Y S , A N D I D E A S F O R
H O W T O E X P A N D T H I S P R O J E C T G O I N G F O R W A R D
Location was the primary factor for selection
Nearly 50% of startups surveyed the workspace chose it because of its location.
Funding needs were at the seed stage
Median funding was just $1MM.
Companies had traction (customers) and business models
Median age of startups was 30 months.
High expectation of churn
At one workspace, the median time in residence was 9 months; and the
total length of time startups expected to stay was 17 months.
Patterns we found in both workspaces
Build to location:
Startups gravitate to each other
and spaces that have other
startups. Building a supportive
ecosystem means going to that
community, not building a
workspace to locate a startup
community in a particular
location to drive outside capital
Bring in the Angels:
Target seed funding for
early stage startups
Startups in workspaces are likely
to be smaller and at the seed
stage. As a result, these startups,
for the most part, are not ready
for venture capital. A robust
Angel Investor community will
provide great impact for seed
Think local & global:
satellite offices are
While it is important to support
local startups, companies seeking
to locate their satellite office in a
workspace offer great benefits to
local startups. Satellite offices of
established startups from outside
a region provide stability, bring in
outside capital, and ideas that
local startups can leverage.
Three insights emerged
1 2 3
Workspace resource guide
Create an online resource with
information about types of workspaces.
Analytic tools Enable workspaces
(startups, investors, policymakers &
workspaces) to compare performance
metrics of workspaces.
Partner with third party
data experts Collaborate with
Angel List and Mattermark to build
automated collection of granular data
Next steps to increase the value of our research
Increase the number of data
points Another year with our partners
and add (1) more partner.
increase frequency of data
collection Collect data on a
Structure data Structure data to
make it more consistent across
Research funding Raise funding to
continue this initiative.
O U R A P P R O A C H : S P L C O L L A B O R A T E D W I T H T W O
W O R K S P A C E S ( S A N F R A N C I S C O & S I L I C O N V A L L E Y )
Partnerships Two workspaces (Runway &
Hacker Dojo) provided access to their community,
promoted the survey, and shared their data.
Time period Research and data collection
occurred between July 2015 - Sept 2015.
Research Methodology Conducted in
person surveys, analyzed member check-in data,
and pulled secondary research.
• Total number of startups surveyed: 80 (Runway:
39, Hacker Dojo: 41)
• Total number of survey respondents: 114
What we did: surveys and research
(Runway: 49, Hacker Dojo: 65)
• Total number of members at Hacker Dojo: 479
• Total number of member check-in data points
• Type of check-in data collected: name, date of
check-in, & time of check-in
Third party data Collected information
about participating startups from Angel List &
Crunchbase, including funding, location, and
expertise Support provided by data science
Our Awesome Workspace partners
For - Profit Non - Profit
Member, month to month,
pay for access to desks
Company, month to month,
pay for individual desks
Mountain Veiw, CASan Francisco, CA
“World's Largest Non-profit
“Runway is a community and co-
working space for entrepreneurs,
influencers, and hustlers”Description
The survey was static, which reduced the depth of insight.
There is a high rate of churn of startups at workspaces. The survey only provides a
snapshot of a moment in time.
Limited financial resources prevent more robust data
collection and analysis.
Robust research requires additional funding to create and maintain infrastructure for
data collection and analysis.
Data accuracy Is heavily dependent on self-reported data.
Data collected was not standardized; proprietary tools might be able to provide more
structure and accuracy, e.g. Mattermark.
A few (massive) caveats about our approach
S U R V E Y F I N D I N G S P R O V I D E A C O M P A R I S O N O F F O R P R O F I T
W O R K S P A C E V E R S U S A N O N - P R O F I T W O R K S P A C E
Member/company time cycle in innovation space
How long are the startups in the
space and how old are they?
Average: 10.87 Months
Median: 9.00 months
Standard deviation: 11.41
Average: 10.03 Months
Median: 8.00 months
Standard deviation: 7.85
Workspaces are perceived as temporary offices.
Most startups have been in the workspace for less than a year.
Funding AmountFunding Amount
$0 to $500,000
$500,000 to $1M
$1M to $1.5M
$1.5M to $3M
what level of funding do these startups have?
Runway Hacker Dojo
The majority of the startups were, unsurprisingly, at the seed stage.
The vast majority of startups had raised less than $500,000.
4 5 4 3
5 1 1 1
price point 4%
collaborative space 4%
investor link 14%
Why do startups select a particular workspace
Runway Hacker Dojo
important in the
work space at
Important in the
makerspaces as well
as the workspace.
Location accounts for
28% of the appeal of
Refers to the availibility
of mentors and
oppertunities in the
A D E E P E R D I V E I N T O T H E I N D I V I D U A L W O R K S P A C E S
R U N W A Y I N C U B A T O R I S A F O R - P R O F I T W O R K S P A C E
L O C A T E D I N S A N F R A N C I S C O ( T W I T T E R B U I L D I N G )
90% of the startups in a general purpose workspace are in software.
B2C and B2B are equally represented, but satellite offices are 30% of residents.
companies @runway have clear characteristics
b2c vs b2b
Why did the company choose runway
Startups chose Runway primarily based on location
How much capital have companies at runway
MEDIAN FUNDING OBTAINED
AVERAGE FUNDING OBTAINED
A few companies skew the data higher.
The vast majority of companies have raised less than $1M — most, in fact, have raised less than $500k.
What are The average and median length of
time companies are located at runway?
Expect high levels of churn at workspaces.
Startups perceive workspaces as a temporary location; with plans to stay for less than two years.
Total Time Since Company
Total Time in Runway
Total Time Estimated to
Be in Runway (months)
H A C K E R D O J O I S a N O N - P R O F I T W O R K S P A C E
L O C A T E D I N M O U N T A I N V I E W
Why did the company choose hacker dojo?
Regardless of the length of time companies expected to spend at Hacker Dojo, Location was the number one reason
for being there.
Length of time
Member Planned to
stay at Hacker Dojo
0 - 3 months
4 - 6 months
6 - 12 months
Equipment Links to
Where hacker dojo members live based on zip code
What is the funding stage and size
of companies at the hacker dojo?
$0 - $50,000 1 - 2
2 - 4
2 - 5
3 - 5
$50,000 - $550,000
$230,000 - $810,000
$260,000 - $610,000
Length of time at Hacker Dojo does not necessarily indicate more funding.
Length of time
to stay at
0 - 3 months
3 - 6 months
6 - 12 months
“low estimate to high estimate” “low estimate to high estimate”
average current company size
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The people behind this project
CEO, Startup Policy Lab
Intern, Startup Policy Lab
DatableApp team on the 1’s and 0’s.
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