This
post was co-written by Sarah Milstein and Eric Ries, co-hosts of The LeanStartup Conference, and cross-posted from Startup Lessons Learned.
It’s
well-known—and we ourselves have been publicly frustrated—that
white men
tend to dominate the speaker rosters for tech and entrepreneurship
conferences,
not to mention the portfolios of many entrepreneurship programs.
Conference
hosts, VC’s, and others often attribute this to a "pipeline problem,"
the idea
that there simply aren’t enough qualified women or people of color who
wanted to or were qualified to participate. So we were proud earlier
this week
to announce our program for The Lean Startup Conference, which comprises
approximately 40% women and 25% people of color. We still have room to grow,
but this is a significant improvement over last year’s conference, which had
almost none of either. Our approach was deliberate, and we want to share
it with you, in the hopes that you can replicate it for other conferences and
for processes like hiring where equity is important.
We have argued previously that the pipeline problem may be caused by the
selection process itself. If under-represented groups have a reasonable expectation of
not being selected, it’s perfectly reasonable that they therefore don’t apply.
After all, if you were thinking of submitting a proposal to present at a
conference that had a record of not choosing people like you—if you weren’t
sure that your proposal would be assessed on its merits or that you’d be
welcome at the event—why would you spend the time applying? The problem
compounds itself: because women and people of color are not often speakers,
we’re less aware of them, and we’re less likely to think of them for our own
events.
There’s
a solution that addresses these issues: meritocratic selection. It’s not a game
of quotas; it’s quite the opposite. Indeed, we picked the speakers we thought
had the best stories and would be the most engaging presenters. We didn’t rule
out any candidates for being white or men, and we didn’t favor women or people
of color. Instead, we used a handful of principles to guide us: transparent
process, blind selection, proactive
outreach and enlisting help. Here’s how they played out.
Transparent process. Over the summer, we made a big
deal about how we wanted to find speakers based on merit (i.e., the great
stories they had to share) rather than on their proximity to us. In August, we
posted a call for speakers,
asking people to apply. We explained that we were
looking for speakers based on what they knew rather than who they knew.
We also
noted that in the past, Eric had mostly drawn from a pool of people he
had worked with directly, which meant that in 2010 and 2011, this
conference had had almost no
speakers typically under-represented at tech events. We received nearly
200
applications, more than half from women and about a quarter from people
of
color. That included a notable number of black people, which we call out
because we’ve received very few applications from black speakers at
other
conferences we’ve run. Similarly, quite a few men and women over the age
of
about 50 applied to speak. One person talked about the importance of
representing
people with disabilities. In addition to being pleased by the
demographic
range, we were stunned by the consistently high quality of the proposed
talk
ideas across groups, as the previous open calls we’ve run have brought
in
relatively few great speakers.
Here’s
what resulted from that call for speakers: from the pool of applicants whom we
chose for the December 3 conference program, more than half were women. From
the pool of applicants whom we chose for the December 2 Ignite: Lean Startup program, more than a third were people of color. And we had to make
some heartbreaking decisions to pass on a number of speakers just because we
didn’t have enough time on stage for everyone. Taken together, this shows that when you have a broader group from
which to draw, there’s a good distribution of speakers; not all—not even
most—of the good speakers are white men. The common conference organizer’s
argument that we don’t know any black people in tech or that women didn’t apply
to speak just doesn’t hold up.
Did
employing a transparent process make a difference? The August call for
proposals described above was actually our second attempt to change the makeup
of our applicant pool; the first attempt failed. In June, we posted our first call for speakers, asking people to nominate others they thought would be good
speakers. We noted that we were particularly keen on learning about women and
people of color who might be great speakers but weren’t on our radar yet, but
we didn’t say anything about what had happened in the past or how we were
trying to change it. We received about 35 nominations. Although some were very
good, just about 10% were women and almost none were people of color. Every
piece of data we have been able to gather on conferences says that 10% is the
standard rate at which women will apply or be nominated and that very few
people of color will be among these pools.
Let’s
dwell on this for a moment. By using principles of meritocratic
selection—i.e., being explicit about our desire to find great speakers whom we
didn’t know, and by being honest about the process we’d used in the past—we
created an atmosphere in which a much broader range of strong speakers felt
invited to participate.
It’s
also worth mentioning that we knew we’d hit on something important not just
because we got such different results in the second round, but also because
applicants told us so. We got a lot of comments like this:
“I
LAUGH when you say, ‘under-represented at a tech conference,’ because had you
not presented such a compelling invitation, I would have never even dreamed of
applying for a position of a speaker.”
“The
main reason I'm applying is because I have a huge amount of respect and
admiration for your efforts to reach out to a new circle of contributors.
Anything I can do to support you, whether it's speaking or just behind the
scenes, is personally very worthwhile to me.”
“Thanks
for opening this up to the non-famous. I think there are lots of great stories
out there to be told.”
Blind review. It’s well documented that when
people know the sex or race of a job applicant or the main character in a story, they generally assess the person’s qualifications and performance more
favorably if the person is male or white. Because we all have internal biases,
everybody does it, including women and people of color. We wanted to eliminate
that bias as best we could. So we asked applicants to submit some written
information, along with a video, and we made the first cut based on the
write-ups, which we read without checking names or other identifying info.
Did
using blind review make a difference? By reading the applications, we quickly
eliminated people who weren’t a fit for the conference because their topic
clearly wasn’t on point for our audience. That was a small group of people, but
the distribution was broad. Beyond that, blind review didn’t make a big
difference. Why? We asked for relatively little info in writing, both because
we wanted to hear directly from speakers (not their PR people) and because
video much better represents the medium we’re trying to assess (often, people
who can write a nice description of their talk can’t deliver the presentation
well, and vice versa). So video was much more important to us than writing, but
we couldn’t assess it blind. It’s worth considering whether there’s more we can
do with this tool in the future.
Proactive outreach. A very common way that
conferences build a program is to brainstorm speakers, come up with a bunch of
familiar names, and then notice late in the game that you have almost no women
or people of color (at which point, you might scramble to find some or just
complain that you don’t know any). Our initial brainstorm wasn’t magically
diverse; in fact, it included an overwhelming percentage of young white men.
But we immediately—during the same meeting—started digging deeper to think of
people we’d left out, and when we came up with less-top-of-mind candidates from
under-represented groups, we reached out to them early and often. We kept that
up throughout the whole cycle.
Did
proactive outreach make a difference? As we noted earlier, Eric’s previous
conferences rosters were based almost entirely on people who were top of mind,
and they skewed heavily toward white and male.
Enlisting help. There were two primary ways we
asked other people to help us. First, when we had a call for participation, we
posted it to mailing lists with lots of women and/or people of color, we asked
our friends to do the same, and we approached organizations like Women 2.0 to publish
or cross-post our info on their blogs and Twitter accounts. Second, when we
asked other people for speaker ideas or when we formed our few panels with
moderators, we told them about our search for under-represented speakers, and
we said that we’d appreciate their support.
Did
enlisting help make a difference? It can be scary to ask for this kind of help,
because you don’t want to suggest that you’re interested in diversity over
quality. But we found that people were consistently, surprising open to working
with us on this issue. And it did make a difference: When we forgot to mention
to people that we were looking for speakers we didn’t already know, we almost
always got back suggestions for more white men who’d be great presenters. When
we included a note about our efforts to reach farther, we almost always got
back suggestions for women and people of color who’d be great presenters. In
addition, we heard regularly from people who’d found out about our call for
speakers through Women 2.0 and other mailing lists we worked with.
--
Our four-pronged
approached generated really encouraging, even exciting, results. We’re further
encouraged by the fact that we didn’t execute this plan perfectly, so there’s
still room for improvement. Here’s what we we’ll work on next time out.
Coordinating our approaches. As noted above, in addition to
our public call for speakers, we also reached out to people we did already know
in the Lean Startup community whom we thought would have really compelling
stories. Although this group included some women and people of color, it had a
big percentage of white men. Because we started this process before the public
call, and because we didn’t know if our public call would work, we quickly
filled a number of speaking slots with these great candidates from the group we
did know, and we didn’t leave as much room as we could have for terrific
speakers new to us. We’ll use a hybrid approach again, but next time, we’ll trust
the open-call process and be more deliberate about the distribution of
speakers.
Getting beyond the easy wins. Related to the issue above, it’s
just plain easier to put people onstage when you know them personally or by
reputation. There are a few reasons for this. First, like most conferences, we
want to put well-known people onstage, because they’re a draw. So when somebody
has a big name and is available, we we’re more likely to consider them for our
program, even if their story is only tangential to our angle. For instance, we
were interested in having some well-known entrepreneurs join us, and we were
willing to let them talk about their experiences generally rather than have
them focus on Lean Startup principles. Unsurprisingly, all of the people who
fit into this category were white men; women and people of color with
comparable stories but less prominence didn’t get this kind of consideration. Correspondingly,
we had much stricter standards for people who were less well known, insisting
that they have a direct Lean Startup story—and if we didn’t already know them, we
were less trusting that their stories were really good examples of Lean Startup
methods. (For the record, we had so many good Lean Startup speakers, we didn’t
wind up taking anybody with a general entrepreneurship story. But we definitely
considered a bunch of them.)
Additionally,
we found that when we already knew a speaker, it was easier to find good slots
for them in the program because we were more aware of how they were using Lean
Startup principles. For instance, if we were looking for somebody from a
hardware startup to tell a great pivot story, we might have had six
candidates…but it just so happened that the one guy we knew from that group had
an even better story about innovation accounting. Because we were familiar with
his company generally, we knew his other areas of expertise, and it was
therefore easier to put him in the program. It was harder to find the various
angles that would work from people we didn’t know.
In other
words, between knowing their stories less well and bringing our biases to bear
in trusting them, we had a harder time green-lighting the people we didn’t
know. Again, that’s human. But if we don’t make conscious decisions to account
for it, we’ll never change the dynamics of these events.
Finding people in other
under-represented groups.
Our program has almost no people of our parents’ generation, and we don’t think
we have any speakers with disabilities. In the future, we can apply the
approach above to find more great speakers from these groups.
--
Pulling
together a conference program that highlights deservedly well-known people
in your field *and* reveals compelling new stories is a challenge. But it’s one
you can take on—and that, frankly, not enough conferences do. As we’ve found, meritocratic selection isn’t
just a phrase you can mull or a fantasy for the future. These tools, used
thoughtfully and in combination, can help you achieve it: transparent process,
blind selection, proactive outreach and enlisting help. And we hope this post will help spark
this question: if you’re not using these tools, is your selection process susceptible to unconscious
biases that could be making it work less well? Is it really as merit-based as it could be?